WO2016058145A1 - 一种用于可穿戴设备脱落检测的方法及可穿戴设备 - Google Patents
一种用于可穿戴设备脱落检测的方法及可穿戴设备 Download PDFInfo
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- WO2016058145A1 WO2016058145A1 PCT/CN2014/088665 CN2014088665W WO2016058145A1 WO 2016058145 A1 WO2016058145 A1 WO 2016058145A1 CN 2014088665 W CN2014088665 W CN 2014088665W WO 2016058145 A1 WO2016058145 A1 WO 2016058145A1
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Definitions
- the embodiments of the present invention relate to the field of information technologies, and in particular, to a method for detecting wearable device dropout and a wearable device.
- the wearable device is a suitable carrier for the wearer's body to communicate with the world because of its light weight and close to the wearer's body.
- Wearable devices can be divided into watches, bracelets, glasses, armbands, ornaments, etc., depending on the product.
- Today, wearable devices are gradually entering people's lives. For example, by wearing wearable devices for children, parents can keep track of their children's whereabouts.
- the wearable device being detached from the wearer indicates that the wearer may be in a hazardous environment, such as a wearable device that forcibly removes the child from a criminal. In this case, the wearable device cannot recognize whether the wearer is likely to be in danger.
- the embodiment of the invention provides a method for the wearable device to fall off detection and a wearable device, which can determine the scene mode described by the wearer after detecting that the wearable device is detached from the wearer, and send a prompt to the outside world. .
- a first aspect discloses a method for wearable device detachment detection, the method comprising:
- determining that the wearable device is detached from the wearer when determining that the wearable device is detached from the wearer, according to the collected physiological parameter information of the wearer of the wearable device And activity information, determining the scene mode in which the wearer is located, specifically:
- the wearable device When it is determined that the wearable device is detached from the wearer, according to the collected wearable Determining, by the ECG signal information of the physiological parameter information of the wearer of the device, whether the wearer's ECG signal information is abnormal; determining whether the wearer is in advance according to the collected active area information of the wearer activity information An activity area is set; determining a scene mode in which the wearer is located according to the collected ECG signal information and the activity area information of the wearer.
- determining that the wearable device is detached from the veneer wearer according to the collected physiological parameters of the wearer of the wearable device Information and activity information, determining the scene mode in which the wearer is located, specifically:
- determining the physiological parameter of the wearer according to the body temperature signal information and the skin resistance signal information of the collected physiological parameter information of the wearer of the wearable device Whether the information is abnormal; determining whether the wearer is in a preset active area according to the collected activity area information of the wearer's activity information; according to the collected body temperature signal information, skin resistance information and activity of the wearer The area information determines the scene mode in which the wearer is located.
- determining that the wearable device is detached from the veneer wearer according to the collected physiological parameters of the wearer of the wearable device Information and activity information, determining the scene mode in which the wearer is located, specifically:
- the surface electromyogram signal sEMG information according to the acquired physiological parameter information of the wearer of the wearable device, the wearer activity of the wearable device, when determining that the wearable device is detached from the claimed wearer Acceleration information of the information, angular velocity information of the wearer's activity information that can be worn by the device, determining whether the wearer's activity state information is abnormal; activity according to the collected wearer's activity information of the wearable device
- the area information determines whether the wearer is located in a preset activity area; and determines a scene mode in which the wearer is located according to the collected activity status information and the activity area information of the wearer.
- the scene modes include one or more of a scene mode with a low dangerous state, a scene mode with a high dangerous state, a scene mode in which the wearable device is normally removed, and a scene mode in which the wearable device is accidentally dropped.
- a second aspect discloses a method for wearable device detachment detection, the method comprising:
- determining the scene mode in which the wearer is located specifically:
- the wearable device When determining that the wearable device is detached from the veneer wearer, according to the collected acceleration information of the wearer activity information of the wearable device and the angular velocity information of the wearer's activity information that can be worn by the device, Determining whether there is an abnormality in the activity status information of the wearer; determining, according to the activity area information of the wearer's activity information, whether the wearer is located in a preset activity area; according to the collected activity status information of the wearer And activity area information, determining a scene mode in which the wearer is located.
- the scenario mode includes: a scenario with a low dangerous state and a scenario with a high dangerous state One or more of a scene mode in which the wearable device is normally removed and a scene in which the wearable device is accidentally dropped.
- a third aspect discloses a wearable device including: a first sensor, a second sensor, a processor, a power source, and a radio frequency circuit, the processor and the first sensor, the second sensor Communicating with the radio frequency circuit, the power supply powering the first sensor, the second sensor, the processor, and the radio frequency circuit, wherein:
- the first sensor is configured to collect physiological parameter information of a wearer of the wearable device
- the processor is configured to determine, according to the first sensor, that the physiological parameter information of the wearer of the wearable device interrupts the abnormality, and when the abnormal time exceeds the preset time, determine that the wearable device is worn from the Fall off
- the second sensor is configured to collect activity information of a wearer of the wearable device
- the processor is further configured to: when the wearable device is detached from the wearer, the physiological parameter information of the wearer of the wearable device and the second sensor according to the first sensor Collecting activity information of the wearer of the wearable device, and determining a scene mode in which the wearer is located;
- a radio frequency circuit configured to, under the control of the processor, send a prompt operation corresponding to the scene mode according to a scenario mode in which the wearer is located.
- the first sensor comprises at least one of an electrocardiographic sensor, a body temperature sensor, a skin resistance sensor, and a myoelectric sensor.
- the first sensor when the first sensor is an electrocardiographic sensor, the second sensor includes a global positioning system (GPS) sensor and One of the Bluetooth sensors; the ECG sensor is configured to collect ECG signal information of the wearer's physiological parameter information;
- GPS global positioning system
- the processor is further configured to: when the wearable device is detached from the wearer, the physiological parameter information of the wearer of the wearable device and the second sensor according to the first sensor Collecting activity information of the wearer of the wearable device, and determining a scene mode in which the wearer is located, specifically:
- the processor when determining that the wearable device is detached from the wearer, determining the wearer according to the ECG signal information of the wearer's physiological parameter information collected by the electrocardiographic sensor Whether there is an abnormality in the ECG signal information; the processor is further configured to determine, according to the activity area information of the wearer's activity information collected by the GPS sensor or the Bluetooth sensor, whether the wearer is in an activity information Preset activity area information;
- the processor is further configured to determine a scene mode in which the wearer is located according to an abnormal condition of the wearer's ECG signal information and active area information.
- the second sensor when the first sensor is a body temperature sensor and the skin resistance sensor, the second sensor includes a GPS One of a sensor and a Bluetooth sensor; the body temperature sensor is configured to collect body temperature signal information of the wearer's physiological parameter information; and the skin resistance sensor is configured to collect skin resistance signal information of the wearer's physiological parameter information;
- the processor is further configured to: when the wearable device is detached from the wearer, the physiological parameter information of the wearer of the wearable device and the second sensor according to the first sensor Collecting activity information of the wearer of the wearable device, and determining a scene mode in which the wearer is located, specifically:
- the processor when determining that the wearable device is detached from the wearer, the wearer's body temperature signal information collected by the body temperature sensor and the wearer collected by the skin resistance sensor The skin resistance signal information is used to determine whether the physiological parameter information of the wearer is abnormal; the processor is further configured to use the activity area information of the wearer's activity information collected by the GPS sensor or the Bluetooth sensor, Determining whether the wearer is in a preset active area letter Information on the activity area of the wearer's activity information;
- the processor is further configured to determine a scene mode in which the wearer is located according to an abnormal condition of the wearer's physiological parameter information and activity area information.
- the second sensor includes three axes when the first sensor is an myoelectric sensor An accelerometer sensor and a gyro sensor, the second sensor further comprising one of a GPS sensor and a Bluetooth sensor; the electromyography sensor is configured to acquire surface electromyogram signal sEMG information of the wearer's physiological parameter information;
- the processor is further configured to: when the wearable device is detached from the wearer, the physiological parameter information of the wearer of the wearable device and the second sensor according to the first sensor Collecting activity information of the wearer of the wearable device, and determining a scene mode in which the wearer is located, specifically:
- the processor when determining that the wearable device is detached from the wearer, is configured to determine, according to information collected by the myoelectric sensor, the three-axis accelerometer sensor, and the gyro sensor An activity status information of the wearer's activity information; the processor is further configured to determine, according to the activity area information of the wearer's activity information collected by the GPS sensor or the Bluetooth sensor, whether the wearer is in an activity Preset activity area information of the information;
- the processor is further configured to determine, according to the activity state information and the activity area information of the wearer, a scene mode in which the wearer is located.
- the scene modes include one or more of a scene mode with a low dangerous state, a scene mode with a high dangerous state, a scene mode in which the wearable device is normally removed, and a scene mode in which the wearable device is accidentally dropped.
- a fourth aspect discloses a wearable device, the wearable device comprising: a first sensor, a second sensor, a processor, a power source, and a radio frequency circuit, the processor and the first sensor, the second sensor Communicating with the radio frequency circuit, the power supply powering the first sensor, the second sensor, the processor, and the radio frequency circuit, wherein:
- the first sensor is configured to collect physiological parameter information of a wearer of the wearable device
- the processor is configured to determine, according to the first sensor, that the physiological parameter information of the wearer of the wearable device is abnormal, and when the abnormal time exceeds a preset time, determine that the wearable device is from the wearer Fall off
- the second sensor is configured to collect activity information of a wearer of the wearable device
- the processor is further configured to determine, according to the activity information of the wearer of the wearable device collected by the second sensor, when the wearable device is detached from the wearer, Situational mode
- a radio frequency circuit configured to, under the control of the processor, send a prompt corresponding to the scene mode according to a scene mode in which the wearer is located.
- the first sensor is a body temperature sensor
- the second sensor includes a three-axis accelerometer sensor and a gyro sensor, and the second sensor further Included as one of a GPS sensor and a Bluetooth sensor
- the body temperature sensor is configured to collect body temperature signal information of the wearer's physiological parameter information
- the processor is further configured to determine, according to the activity information of the wearer of the wearable device collected by the second sensor, when the wearable device is detached from the wearer,
- the scene mode is as follows:
- the processor is further configured to: when the wearable device is detached from the wearer, an activity state of the wearer's activity information collected according to the three-axis accelerometer sensor and the gyro sensor Determining whether there is an abnormality in the activity status information of the wearer's activity information; the processor is further configured to determine, according to the activity area information of the wearer's activity information collected by the GPS sensor or the Bluetooth sensor Whether the activity information of the wearer is in preset activity area information;
- the processor is further configured to determine, according to the activity state information and the activity area information of the wearer, a scene mode in which the wearer is located.
- the scenario mode includes: a scenario with a low dangerous state and a scenario with a high dangerous state One or more of a scene mode in which the wearable device is normally removed and a scene in which the wearable device is accidentally dropped.
- a method for detecting wearable device fall-off is provided by the embodiment of the present invention, by collecting physiological parameter information and activity information of a wearer of the wearable device; and detecting wearing of the wearable device
- the physiological parameter information of the person is abnormal, and when the abnormal time exceeds the preset time, it is determined that the wearable device is detached from the wearer; when it is determined that the wearable device is detached from the wearer, according to the collected Determining a profile of the wearer in the physiological parameter information and activity information of the wearer of the wearable device; sending according to the profile mode in which the wearer is located
- the prompt corresponding to the scene mode can determine the scene mode described by the wearer after detecting that the wearable device is detached from the wearer, and issue a prompt to the outside world.
- FIG. 1 is a schematic diagram of a method for detecting wear-off of a wearable device according to an embodiment of the present invention
- FIG. 2 is a schematic diagram of still another method for detecting wear-off of a wearable device according to an embodiment of the present invention
- FIG. 3 is a schematic diagram of still another method for detecting wear-off of a wearable device according to an embodiment of the present invention
- FIG. 4 is a schematic diagram of still another method for detecting wearable device dropout according to an embodiment of the present invention.
- FIG. 5 is a schematic diagram of still another method for detecting wear-off of a wearable device according to an embodiment of the present invention.
- FIG. 6 is a schematic structural diagram of a wearable device according to an embodiment of the present invention.
- FIG. 7 is a schematic structural diagram of still another wearable device according to an embodiment of the present invention.
- FIG. 7 is a schematic structural diagram of still another wearable device according to an embodiment of the present invention.
- FIG. 8 is a schematic structural diagram of still another wearable device according to an embodiment of the present invention.
- FIG. 8 is a schematic structural diagram of still another wearable device according to an embodiment of the present invention.
- FIG. 9 is a schematic structural diagram of still another wearable device according to an embodiment of the present invention.
- FIG. 9 is a schematic structural diagram of still another wearable device according to an embodiment of the present invention.
- FIG. 10 is a schematic structural diagram of still another wearable device according to an embodiment of the present invention.
- FIG. 10 is a schematic structural diagram of still another wearable device according to an embodiment of the present invention.
- the wearable devices of the embodiments of the present invention include a watch, a wristband, a glass, an armband, and an electronic device integrated into a garment, a shoe, a sock, a helmet, a hat, and the like.
- Fluctuations in human emotions can affect physiological parameters such as pulse and body temperature. For example, mental stress and emotional excitement can accelerate the pulse rate and increase the body temperature. Therefore, it is possible to judge the fluctuation of the person's mood by monitoring some physiological parameters of the person.
- the fluctuation of people's emotions can reflect the change of people's environment to a certain extent. For example, the wearer has a rapid heartbeat, elevated body temperature, etc., indicating that the wearer may be in a dangerous environment.
- FIG. 1 is a schematic diagram of a method for detecting wear-off of a wearable device according to an embodiment of the present invention.
- the execution body of the method 100 may be a wearable device.
- the method 100 includes the following steps:
- S102 Collect physiological parameter information and activity information of a wearer of the wearable device.
- human physiological parameter information includes ECG signal, body temperature, skin resistance, surface electromyography (SEMG), EEG signal (Electroencephalograph, EEG), etc., ECG signal information including heart rate , sinus beats and other information.
- Activity information includes activity status information and activity area information.
- ECG signal information can be collected by ECG sensor in real time or timing; body temperature signal information can be collected by real-time or timed by body temperature sensor; skin resistance information can be collected by skin resistance sensor in real time or timing; sEMG signal information can be real-time through EMG sensor Or timed collection.
- arm motion and/or gesture motion information of the wearer's activity state information can be determined.
- the acceleration information of the activity status information can be acquired by the three-axis accelerometer sensor in real time or at a time; the angular velocity information of the activity state information can be collected in real time or by the gyro sensor; the active area information can be passed through the Global Position System (GPS).
- GPS Global Position System
- the sensor or Bluetooth sensor is acquired in real time or at a fixed time.
- the Bluetooth sensor refers to a device that supports short-range wireless communication technology, and can exchange wireless information between a mobile phone, a palmtop computer, a wireless headset, a notebook computer, a wearable device, and the like.
- the Bluetooth sensor can be specifically a Bluetooth chip.
- S104 It is detected that the physiological parameter information of the wearer of the wearable device is abnormal, and when the abnormal time exceeds a preset time, determining that the wearable device is detached from the wearer.
- physiological parameter information can be collected by different sensors.
- the preset time can be set to different preset times depending on the type of sensor. It can also be set to a uniform preset time, for example, the preset time is 5 seconds.
- the specific preset time can be set according to actual needs. Anomalies include situations where the acquired signal is interrupted.
- the scene mode in which the wearer is located includes one or more of a scene mode with a low dangerous state, a scene mode with a high dangerous state, a scene mode in which the wearable device is normally removed, and a scene mode in which the wearable device is accidentally dropped.
- S108 Send a prompt corresponding to the scene mode according to the scene mode in which the wearer is located.
- the prompt corresponding to the scenario is specifically:
- an emergency call may be placed to a preset mobile number in the wearable device, or an emergency alert message may be sent; or an alarm or mobile phone paired with the wearable device may be issued.
- the emergency reminder information may also be that the wearable device itself issues a prompt, such as the wearable device sounding an alarm sound.
- the help information may be sent to the mobile phone paired with the wearable device; the help information may also be sent to the alarm paired with the wearable device; or the wearable device may be The user itself issues a prompt, such as the wearable device sounds an alarm.
- the mobile phone paired with the wearable device may be issued with the information that the wearable device accidentally falls off; or the wearable device that is paired with the wearable device may be issued.
- the accidental disconnection prompt message may also be that the wearable device itself issues a prompt, such as the wearable device sounding an alarm sound.
- the wearable device may not issue a prompt message; and may also issue a normal removal prompt message.
- a method for detecting wear-off of a wearable device by the embodiment of the present invention by collecting physiological parameter information and activity information of a wearer of the wearable device; and detecting abnormality of physiological parameter information of the wearer of the wearable device, And when the abnormal time exceeds the preset time, determining that the wearable device is detached from the wearer; when determining that the wearable device is detached from the wearer, according to the collected Determining the physiological parameter information and activity information of the wearer of the wearable device, or determining the scene mode in which the wearer is located according to the collected activity information of the wearer of the wearable device; sending according to the scene mode in which the wearer is located
- the prompt corresponding to the scene mode can determine the scene mode described by the wearer after detecting that the wearable device is detached from the wearer, and issue a prompt to the outside world.
- FIG. 2 is a schematic diagram of a method 200 for wearable device drop detection according to an embodiment of the present invention.
- the execution device of the method 200 may be a smart watch including a processor, an electrocardiogram sensor, and a GPS sensor. And one of the Bluetooth sensors, the RF circuit.
- the ECG sensor is configured to collect ECG signal information of physiological parameter information of a wearer of the smart watch; the GPS sensor or the Bluetooth sensor is used to collect active area information of the wearer's activity information.
- the ECG sensor can collect information such as the wearer's heart rate and sinus beats.
- an electrocardiographic sensor is used to collect the sinus heart beat of the wearer as an example for description.
- the method 200 for detecting wear-off of the wearable device provided by the embodiment of the present invention can determine the scene mode described by the wearer after detecting that it is detached from the wearer, and issue a prompt to the outside world.
- the specific steps are as follows:
- S202 The electrocardiogram sensor is used to collect the sinus beat of the wearer of the smart watch.
- the ECG sensor can collect the sinus beat information of the wearer's ECG signal information in real time or at a time.
- the ECG signal information belongs to the physiological parameter information of the wearer.
- a GPS sensor or a Bluetooth sensor is used to collect activity area information of a wearer of the smart watch.
- the GPS sensor or the Bluetooth sensor can acquire the active area information of the wearer of the smart watch in real time or at a time.
- the wearer's activity area information refers to the position where the wearer is currently located, for example, the wearer is at school, or the wearer is at home.
- the processor determines that the smart watch wearer's ECG signal information is abnormal according to the ECG sensor, and when the abnormal time exceeds the preset time, determining that the smart watch is detached from the wearer.
- the preset time may be 5 seconds.
- the processor detects that the wearer's ECG signal information is abnormal, and the abnormal time exceeds 5 seconds, and the processor determines that the smart watch is detached from the wearer.
- the specific preset time value can be determined according to actual needs.
- the anomaly includes an interrupted signal acquisition.
- the ECG signal information is interrupted for more than 5 seconds.
- the processor determines, when the smart watch is detached from the wearer, whether the sinus beat information of the wearer is abnormal according to the wearer's sinus beat information collected by the electrocardiographic sensor; the processor is further configured according to The activity area information of the wearer collected by the GPS sensor or the Bluetooth sensor determines whether the wearer's active area is in a preset active area; the processor according to the wearer's sinus Sexual heartbeat information and activity area information determine the scene mode in which the wearer is located.
- the preset active area may be a safe activity area of the wearer.
- the radio frequency circuit of the smart watch is used to send a prompt corresponding to the scene mode according to the scene mode of the wearer under the control of the processor of the smart watch.
- step S208 the processor determines whether the wearer's sinus beat information is abnormal, and includes the following steps:
- Step 2081 The processor analyzes the sinus beat information detected by the electrocardiographic sensor within a specified period of time before the smart watch is detached from the wearer.
- the specified time can be 10 minutes.
- the specific time period value can be set according to actual needs.
- Step 2082 The above specified time period is divided into preset M time segments, and M is a positive integer.
- the above specified time period is divided into two time periods, the first time period is 1 to 5 minutes; the second time period is 6th to 10th minutes.
- Calculate the time interval between each adjacent two sinus beats in the first time period, and then calculate the average value of the above time intervals in the first time period, recorded as Calculate the time interval between each adjacent two sinus beats in the second time period, and then calculate the average value of the above time intervals in the second time period, recorded as The number M of the specific time period can be set according to actual needs.
- Step 2083 Calculate the standard deviation (Standard Deviation, SD for short) of the time interval of the sinus beats in the above M time periods.
- the standard deviation is calculated as:
- N is the number of sinus beats detected in the corresponding time period
- t i is the time interval of the i-th adjacent two sinus beats in the corresponding time period
- It is the average of the time intervals of the sinus beats in the corresponding time period.
- the standard deviation of the time interval of sinus beats during the first time period is x 1
- the standard deviation of the time interval of sinus beats during the second time period is x 2 .
- Step 2084 Determine whether the rate of change of the average of the time intervals of the sinus beats in different time periods exceeds a specified average threshold ⁇ 1 .
- the specified average threshold ⁇ 1 may be 0.15.
- the specific specified average threshold ⁇ 1 can be set according to actual needs. The judgment formula is:
- Step 2085 Determine whether the rate of change of the standard deviation of the time interval of the sinus beats in different time periods exceeds the specified standard deviation threshold ⁇ 2 .
- the specified standard deviation threshold ⁇ 2 may be 0.1.
- the specific specified standard deviation threshold ⁇ 2 can be set according to actual needs. The judgment formula is:
- step S208 the processor determines whether the active area of the wearer is in a preset active area, specifically:
- the processor determines whether the active area of the wearer is in a preset active area according to the activity area information of the wearer collected by the GPS sensor or the Bluetooth sensor.
- the preset active area is the wearer's safe activity area.
- the wearer is in the preset active area under the following conditions.
- the current time is the school time
- the GPS sensor positioning result is the position of the wearer as the school
- the current time is the time of the school or the time of the wearer going to school.
- the GPS sensor positioning result is that the wearer is in the preset school or school path;
- the result is the distance between the wearer and the supervisor.
- the specified distance may be 10 meters.
- the wearer is in a non-preset activity area under the following conditions:
- the current time is the school time, and the GPS sensor positioning result is that the wearer is located outside the school;
- the current time is the time of the school or the time of the wearer going to school.
- the GPS sensor positioning result is that the wearer is in an area outside the preset school or school path;
- the wearer's wearable device pairing the wearer's wearable device with the supervisor's mobile phone or an alarm, and at the current time, by the Bluetooth sensor with the mobile phone or the alarm, the distance between the wearer and the supervisor exceeds Specify a distance, for example, the specified distance can be 10 meters.
- step S208 the processor determines, according to the wearer's sinus beat information and the activity area information, the scene mode in which the wearer is located, specifically:
- the GPS sensor positioning result shows that the current position of the wearer when the smart watch is off does not match the safety activity area corresponding to the current time. For example, the time when the smart watch falls off is the school time, and the safety activity area corresponding to the current time is the school, GPS.
- the sensor positioning result shows that the position of the wearer is not in the school, so the wearer's active area is abnormal.
- the processor of the smart watch combines the wearer's HRV information and the activity area information to determine that the current mode of the wearer is "a scene in which the wearer is in a dangerous state.”
- the GPS sensor positioning result shows that the current position of the wearer when the smart watch is detached matches the safe activity area corresponding to the current time. For example, the time when the smart watch falls off is the school time, and the safety activity area corresponding to the current time is the school, GPS.
- the sensor positioning result shows that the wearer is in the school, so the wearer's active area is normal.
- the processor of the wearable device combines the HRV information and the activity area information of the wearer to determine that the current mode of the wearer is “a scene mode in which the wearer is in a dangerous state”.
- the GPS sensor positioning result shows that the current position of the wearer when the smart watch is off does not match the safety activity area corresponding to the current time. For example, the time when the smart watch falls off is the school time, and the safety activity area corresponding to the current time is preset.
- the GPS sensor positioning result shows that the position of the wearer is not in the home route, so the wearer's active area is abnormal.
- the processor of the wearable device combines the HRV information and the activity area information of the wearer to determine that the current mode of the wearer is “a scene mode in which the wearer is accidentally dropped by the wearable device”.
- the GPS sensor positioning result shows that the current position of the wearer when the smart watch comes off matches the safe activity area corresponding to the current time. For example, the time when the smart watch falls off is the night rest time, and the safe activity area corresponding to the current time is the home, GPS.
- the sensor positioning result shows that the wearer is at home, so the wearer's active area is normal.
- the processor of the wearable device combines the HRV information and the activity area information of the wearer to determine that the current mode of the wearer is “a scene mode in which the wearer is normally removed by the wearable device”.
- the processor determines, according to the wearer's sinus beat information and the activity area information, the scene mode in which the wearer is located, and may also be:
- the GPS sensor positioning result shows that the current position of the wearer when the smart watch is off does not match the safety activity area corresponding to the current time. For example, the time when the smart watch falls off is the school time, and the safety activity area corresponding to the current time is the school, GPS.
- the sensor positioning result shows that the position of the wearer is not in the school, so the wearer's active area is abnormal.
- the processor of the smart watch combines the wearer's HRV information and the activity area information to determine that the current mode of the wearer is "a scene in which the wearer is in a dangerous state.”
- the GPS sensor positioning result shows that the current position of the wearer when the smart watch is detached matches the safe activity area corresponding to the current time. For example, the time when the smart watch falls off is the school time, and the safety activity area corresponding to the current time is the school, GPS.
- the sensor positioning result shows that the wearer is in the school, so the wearer's active area is normal.
- the processor of the wearable device combines the HRV information and the activity area information of the wearer to determine that the current mode of the wearer is “a scene mode in which the wearer is in a dangerous state”.
- the GPS sensor positioning result shows that the current position of the wearer when the smart watch is off does not match the safety activity area corresponding to the current time. For example, the time when the smart watch falls off is the school time, and the safety activity area corresponding to the current time is preset.
- the GPS sensor positioning result shows that the position of the wearer is not in the home route, so the wearer's active area is abnormal.
- the processor of the wearable device combines the HRV information and the activity area information of the wearer to determine that the current mode of the wearer is “a scene mode in which the wearer is in a dangerous state”.
- the GPS sensor positioning result shows that the current position of the wearer when the smart watch comes off matches the safe activity area corresponding to the current time. For example, the time when the smart watch falls off is the night rest time, and the safe activity area corresponding to the current time is the home, GPS.
- the sensor positioning result shows that the wearer is at home, so the wearer's active area is normal.
- the processor of the wearable device combines the HRV information and the activity area information of the wearer to determine that the current mode of the wearer is “a scene mode in which the wearer is accidentally dropped by the wearable device”.
- step S210 the radio frequency circuit of the smart watch is used to send a prompt corresponding to the scene mode according to the scene mode of the wearer under the control of the processor of the smart watch, specifically:
- the radio frequency circuit of the smart watch can issue an emergency call to the preset mobile phone number in the wearable device, or issue an emergency prompt message; the radio frequency circuit of the smart watch also An emergency alert message may be sent to an alarm paired with the wearable device, or the radio frequency circuit of the smart watch may issue help information to a mobile phone paired with the wearable device; the smart watch itself may also issue a prompt, such as the smart watch An alarm sounds.
- the smart watch's radio frequency circuit can send help information to the mobile phone paired with the wearable device; the smart watch's radio frequency circuit can also pair with the wearable device.
- the alarm sends out help information; the smart watch itself can also issue a prompt, such as the smart watch sounds an alarm.
- the radio frequency circuit of the smart watch may send a message indicating that the wearable device is accidentally detached to the mobile phone paired with the wearable device; the radio frequency circuit of the smart watch may also Sending a wearable device meaning to an alarm paired with the wearable device
- the radio frequency circuit of the smart watch may not issue a prompt message; the radio frequency circuit of the smart watch may also issue a normal removal prompt message.
- the ECG sensor is used to collect the wearer's heart rate information to determine whether the wearer's physiological parameter information is abnormal, the scheme and the ECG sensor collect the wearer's sinus heartbeat.
- the method for detecting wearable device drop detection provided by the embodiment of the present invention can determine the scene mode described by the wearer after detecting that the smart watch is detached from the wearer, and issue a prompt to the outside world.
- FIG. 3 is a schematic diagram of a method 300 for detecting wear-off of a wearable device according to an embodiment of the present invention.
- the execution device of the method 300 can be a smart wristband. Another method for detecting wearable device dropout will be described.
- the smart bracelet includes a processor, a first sensor, a second sensor, and a radio frequency circuit.
- the first sensor of the smart bracelet includes a body temperature sensor for detecting body temperature signal information in a physiological parameter of the wearer, and a skin resistance sensor for detecting skin resistance signal information in the physiological parameter of the wearer;
- the second sensor includes one of a GPS sensor and a Bluetooth sensor for collecting active area information of the wearer's activity information.
- the body temperature sensor is used to collect the body temperature signal information of the wearer of the smart bracelet; the skin resistance sensor is used to collect the skin resistance information of the wearer of the smart bracelet.
- the body temperature sensor can collect the body temperature signal information of the wearer of the smart bracelet in real time or at a time; the skin resistance sensor can collect the skin resistance information of the wearer of the smart bracelet in real time or at a time. Wherein, the body temperature signal information and the skin resistance signal information belong to the physiological parameter information of the wearer.
- a GPS sensor or a Bluetooth sensor is used to collect activity area information of the wearer of the smart bracelet.
- the GPS sensor or the Bluetooth sensor can collect the active area information of the wearer of the smart bracelet in real time or at a time.
- the wearer's activity area information refers to the position where the wearer is currently located, for example, the wearer is at school, or the wearer is at home.
- the processor detects the body temperature signal information of the wearer of the smart bracelet according to the body temperature sensor. When the abnormality is exceeded and the abnormal time exceeds the preset time, it is judged that the smart bracelet is detached from the wearer.
- the processor determines that the smart bracelet is detached from the wearer's body by detecting that the wearer's body temperature signal is abnormal by the body temperature sensor, and the abnormal time exceeds a preset time, for example, 3 seconds, or the measured value of the wearer's body temperature signal is detected.
- a preset time for example, 3 seconds, or the measured value of the wearer's body temperature signal is detected.
- the specified body temperature threshold for example, the specified body temperature threshold is 26 ° C; the processor determines that the smart bracelet is detached from the wearer's body, and the skin resistance signal abnormality is detected by the skin resistance sensor, and the abnormal time exceeds the preset time. For example, for 3 seconds, the processor determines that the smart bracelet is detached from the wearer.
- the processor determines, according to the body temperature signal information of the wearer collected by the body temperature sensor and the skin resistance signal information of the wearer of the wearer, when determining that the smart bracelet is detached from the wearer. Whether the physiological parameter information of the wearer is abnormal; the processor further determines, according to the activity area information of the wearer's activity information collected by the GPS sensor or the Bluetooth sensor, whether the wearer is in a preset active area; The wearer's physiological parameter information and the activity area information determine the scene mode in which the wearer is located.
- the preset active area is a safe activity area of the wearer.
- the radio frequency circuit of the smart bracelet is used to send a prompt corresponding to the scene mode according to the scene mode of the wearer under the control of the processor of the smart bracelet.
- step S308 the processor determines whether the physiological parameter information of the wearer is abnormal, and includes the following steps:
- Step 3081 The processor of the smart bracelet analyzes the body temperature signal of the wearer collected by the body temperature sensor within a specified period of time before the smart bracelet is detached from the wearer.
- the duration of the specified time period can be 2 minutes, and the specific duration can be determined according to actual needs.
- the processor of the smart bracelet analyzes the body temperature signal collected by the body temperature sensor within 2 minutes before the smart bracelet is detached from the wearer.
- the average value of the body temperature signal in the first minute is t 1
- the average value of the body temperature signal in the second minute is t 2 . If
- ⁇ t can be taken as 0.5 °C.
- the value of ⁇ t can be determined according to actual needs.
- Step 3082 The processor of the smart bracelet analyzes the skin resistance signal of the wearer collected by the skin resistance sensor within a specified period of time before the smart bracelet is detached from the wearer.
- the duration of the specified time period may be 2 minutes, and the specific time period is determined according to actual needs.
- the processor of the smart bracelet analyzes the skin resistance signal collected by the skin resistance sensor within 2 minutes before the smart bracelet is detached from the wearer.
- the processor of the smart bracelet calculates an average value ⁇ and an average standard deviation ⁇ of the skin resistance signals detected during the specified time period. First dividing the specified time period into multiple time windows, The width of this time window is the default value. For example, the width of the time window is preset to 10 seconds.
- the average of the skin resistance signals collected during each time window is then calculated. If the average value of the skin resistance signals in three consecutive time windows is outside the interval range [ ⁇ -3 ⁇ , ⁇ +3 ⁇ ], the processor of the smart bracelet determines the skin resistance signal of the wearer. Abnormal.
- step S308 the processor determines whether the active area of the wearer is in a preset active area. For details, refer to the division of the preset active area of the wearer of the smart watch in step S208.
- step S308 the processor determines the scene mode in which the wearer is located according to the physiological parameter information and the activity area information of the wearer, and the recognition result of the scene mode is as shown in the scene pattern recognition result of Table 1:
- step S310 the radio frequency circuit of the smart bracelet is used to send a prompt corresponding to the scene mode according to the scene mode of the wearer under the control of the processor of the smart bracelet, and the specific implementation manner See the description of the prompts sent in step S210 corresponding to the context mode in the smart watch embodiment above.
- the method 300 provided by the embodiment of the present invention can determine the scene mode described by the wearer after detecting that the smart bracelet is detached from the wearer, and issue a prompt to the outside world.
- FIG. 4 illustrates yet another method 400 for wearable device drop detection according to an embodiment of the present invention.
- the execution device of the method 400 may be another smart wristband.
- the smart bracelet includes a processor, a first sensor, a second sensor, and a radio frequency circuit.
- the first sensor of the smart bracelet is a body temperature sensor for detecting body temperature signal information in a wearer's physiological parameters;
- the second sensor comprises a three-axis accelerometer sensor and a gyro sensor, the second sensor further comprising a GPS sensor And one of the Bluetooth sensors.
- a three-axis accelerometer sensor in the second sensor is used to collect acceleration information of the wearer's activity state information;
- a gyroscope sensor is used to collect angular velocity information of the wearer's activity state information; a GPS sensor or Bluetooth in the second sensor
- the sensor is used to detect active area information of the wearer's activity information.
- the method 400 provided by the embodiment of the present invention can determine the scene mode described by the wearer after detecting that the smart bracelet is detached from the wearer, and issue a prompt to the outside world. The specific steps are as follows:
- the body temperature sensor is used to collect the body temperature signal information of the wearer of the smart bracelet.
- the body temperature sensor can collect the body temperature signal information of the wearer of the smart bracelet in real time or at a time. Wherein, the body temperature signal information belongs to the physiological parameter information of the wearer.
- S404 The processor determines that the body temperature signal information of the wearer of the smart bracelet is abnormal according to the body temperature sensor, and when the abnormal time exceeds the preset time, determining that the smart bracelet is detached from the wearer.
- the body temperature sensor of the smart bracelet detects that the body temperature signal of the wearer is abnormal, and the abnormal time exceeds a preset time, for example, 3 seconds, or detects that the measured value of the wearer's body temperature signal is lower than a specified body temperature threshold, for example, a specified body temperature threshold.
- the processor of the smart bracelet determines that the smart bracelet is detached from the wearer.
- the three-axis accelerometer sensor is used to collect the wearer's acceleration information; the gyro sensor is used to collect the wearer's angular velocity information; and the GPS sensor or the Bluetooth sensor is used to collect the wearer's active area information.
- the activity information of the wearer includes activity status information and activity area information.
- the wearer's activity status information includes the wearer's acceleration information determined by the three-axis accelerometer sensor and the wearer's angular velocity information as determined by the gyro sensor.
- the three-axis accelerometer sensor can collect the wearer's acceleration information in real time or at a time; the gyro sensor can collect the wearer's angular velocity information in real time or at a time; the GPS sensor or the Bluetooth sensor can collect the wearer's active area information in real time or at a time.
- the processor when determining that the smart bracelet is detached from the wearer, according to the activity status information of the wearer's activity information collected by the three-axis accelerometer sensor and the gyro sensor, Determining whether the wearer's activity status information is abnormal; the processor further determining, according to the GPS area sensor or the activity area information of the wearer's activity information collected by the Bluetooth sensor, whether the wearer is in a preset active area; The device determines the scene mode in which the wearer is located based on the wearer's activity state information and the activity area information.
- the preset active area is a safe activity area of the wearer.
- the radio frequency circuit of the smart bracelet is used to send a prompt corresponding to the scene mode according to the scene mode of the wearer under the control of the processor of the smart bracelet.
- step S408 the processor determines, according to the activity state information of the wearer's activity information collected by the three-axis accelerometer sensor and the gyro sensor, whether the wearer's activity state information is abnormal.
- the specific steps are as follows:
- Step 4081 The processor of the smart bracelet analyzes the acceleration information of the wearer collected by the three-axis accelerometer sensor within a specified time period before the smart bracelet is detached.
- the duration of the specified time period may be 1 minute, and the specific time period may be determined according to actual needs.
- the resultant acceleration is calculated based on the acceleration measurements on each axis acquired by the three-axis accelerometer sensor.
- the calculation formula is:
- a x is the acceleration measurement of the three-axis accelerometer sensor in the x-axis direction
- a y is the acceleration measurement of the three-axis accelerometer sensor in the y-axis direction
- a z is the acceleration of the three-axis accelerometer sensor in the z-axis direction
- the measured value, a is the combined acceleration.
- Step 4082 Compare the combined acceleration a with the specified acceleration threshold ⁇ a to determine whether the combined acceleration a is greater than the specified acceleration threshold ⁇ a .
- Step 4083 Calculate the tilt angle ⁇ of the wearer's smart bracelet and compare it with the specified tilt angle threshold ⁇ ⁇ to determine whether the tilt angle ⁇ of the smart bracelet is greater than the specified tilt angle threshold ⁇ ⁇ .
- the calculation formula of the inclination angle ⁇ is:
- a is the combined acceleration calculated in step 4081;
- Step 4084 The processor of the smart bracelet analyzes the angular velocity signal collected by the gyro sensor within a specified period of time before the smart bracelet is detached from the wearer. By analyzing the angular velocity signal information, it is determined whether the smart bracelet has periodic oscillations.
- Step 4085 Combining the analysis results of step 4083 and step 4084, the wearer's activity state is divided into the active state normal state and the active state abnormality, and the result is shown in the activity state judgment result of Table 3:
- Step 4068 The processor of the smart bracelet determines whether the wearer is in the preset active area by analyzing the information collected by the GPS sensor or the Bluetooth sensor.
- the specific preset activity area refer to the smart watch embodiment, and step S208 The division of the preset active area of the wearer of the smart watch.
- the preset active area is a safe activity area of the wearer.
- step S408 the processor determines the scene mode in which the wearer is located according to the wearer's activity state information and the activity area information, and the scene mode recognition result is as shown in the table 4 scene pattern recognition result:
- step S410 the radio frequency circuit of the smart bracelet is used to send a prompt corresponding to the scene mode according to the scene mode of the wearer under the control of the processor of the smart bracelet, and the specific implementation manner See the description of the prompts sent in step S210 corresponding to the context mode in the smart watch embodiment above.
- Another method 400 for detecting wearable device dropout provided by the embodiment of the present invention is detecting After the smart bracelet is detached from the wearer, the scene pattern described by the wearer can be judged and a prompt is issued to the outside world.
- FIG. 5 illustrates yet another method 500 for wearable device drop detection according to an embodiment of the present invention.
- the execution device of the method 500 may be a smart armband.
- a smart armband is taken as an example to describe a method for detecting wearable device dropout provided by an embodiment of the present invention.
- the smart armband includes a processor, a first sensor, a second sensor, and a radio frequency circuit.
- the first sensor of the smart armband is an electromyography sensor for detecting the surface electromyogram signal sEMG of the wearer.
- the second sensor includes a three-axis accelerometer sensor and a gyro sensor, the second sensor further including one of a GPS sensor and a Bluetooth sensor.
- the three-axis accelerometer sensor and the gyro sensor in the second sensor are used to collect activity state information of the wearer's activity information; the GPS sensor and the Bluetooth sensor in the second sensor are used to detect the active area of the wearer's activity information. information.
- the physiological basis for recognizing the wearer's gestures using the sEMG signal is that the movement of a particular joint of the limb is controlled by its corresponding muscle group. Because the sEMG signal can not only reflect the joint flexion and extension and flexion strength, but also reflect the shape, position, orientation and movement information of the hand during the gesture. In addition, using the sEMG signal collected from the corresponding muscle group, Identify gestures including upper limb forearm motion, elbow joint motion, wrist joint motion, and finger motion. Among them, the finger movement includes a single-finger action and a combined finger action. For example, wrist movements include stretching exercises, flexing wrist movements, positive palm movements, and back palm movements.
- the method 500 for the wearable device off detection provided by the embodiment of the present invention can determine the scene mode described by the wearer after detecting that the smart armband is detached from the wearer, and issue a prompt to the outside world.
- the specific steps are as follows:
- the myoelectric sensor collects sEMG signal information of the wearer of the smart armband.
- the myoelectric sensor can acquire the sEMG signal information of the wearer of the smart armband in real time or at a time.
- the sEMG signal information belongs to the physiological parameter information of the wearer.
- the processor determines that the sEMG signal information of the wearer of the smart armband is abnormal according to the myoelectric sensor, and when the abnormal time exceeds the preset time, determining that the smart armband is detached from the wearer.
- the smart armband's myoelectric sensor detects the wearer's sEMG signal abnormality, and the abnormal time exceeds a preset time, for example, 5 seconds, the processor of the smart armband determines that the smart armband is detached from the wearer.
- the three-axis accelerometer sensor is used to collect the wearer's acceleration information; the gyro sensor Used to collect the angular velocity information of the wearer; the GPS sensor or the Bluetooth sensor is used to collect the active area information of the wearer.
- the activity information of the wearer includes activity status information and activity area information.
- the wearer's activity status information includes the wearer's gesture motion and/or arm motion information determined by the myoelectric sensor, the wearer's acceleration information determined by the triaxial accelerometer sensor, and the wearer's angular velocity information determined by the gyro sensor. .
- the three-axis accelerometer sensor can collect the wearer's acceleration information in real time or at a time; the gyro sensor can collect the wearer's angular velocity information in real time or at a time; the GPS sensor or the Bluetooth sensor can collect the wearer's active area information in real time or at a time.
- the processor determines, when the smart armband is detached from the wearer, the wearer's activity state information according to the smart armband's myoelectric sensor, the three-axis accelerometer sensor, and the gyro sensor. Whether there is an abnormality in the active state; the processor further determines whether the wearer is in a preset active area according to the activity area information of the wearer collected by the GPS sensor or the Bluetooth sensor of the smart armband; and the processor according to the activity state of the wearer Information and activity area information to determine the scene mode in which the wearer is located.
- the preset active area is a safe activity area of the wearer.
- the radio frequency circuit of the smart armband is used to send a prompt corresponding to the scene mode according to the scene mode of the wearer under the control of the processor of the smart armband.
- step S508 the processor determines, according to the activity state information of the wearer's activity information collected by the smart armband's myoelectric sensor, the three-axis accelerometer sensor, and the gyro sensor, whether the wearer's activity state is abnormal. Specifically:
- the processor of the smart armband performs pattern recognition on the signal information of the wearer collected by the myoelectric sensor, the three-axis accelerometer sensor and the gyro sensor, and performs the pattern recognition result and the arm movement and gesture action preset by the smart armband. Compare to determine if the two match. Among them, the preset arm movements and gesture actions correspond to different activity states of the wearer. If the processor of the smart armband determines that the current arm motion and/or gesture motion of the wearer is successfully matched with the preset arm motion and gesture motion, the current active state of the wearer can be determined.
- the processor of the smart armband analyzes the signals collected by the myoelectric sensor, the three-axis accelerometer sensor, and the gyro sensor, and finds that the current arm movement and/or gesture action of the wearer may be abnormal, and the processor passes the above.
- the collected signal is subjected to pattern recognition, and the pattern recognition result is compared with the data corresponding to the preset arm motion and the gesture motion, and it is determined that the current arm motion and/or the gesture motion of the wearer is the wrist arm rearward swing arm.
- Intelligent The armband's processor determines that the wearer's current active state is abnormal.
- step S508 the processor determines, according to the GPS sensor of the smart armband or the active area information of the wearer's activity information collected by the Bluetooth sensor, whether the wearer is in a preset active area, as shown in FIG.
- the division of the preset active area of the wearer of the smart watch in step S208 is performed.
- the preset active area is a safe activity area of the wearer.
- step S508 the processor determines the scene mode in which the wearer is located according to the wearer's activity state information and the activity area information, and the recognition result of the scene mode is as shown in Table 4 and Table 5.
- step S510 the radio frequency circuit of the smart armband is used to send a prompt corresponding to the scene mode according to the scene mode of the wearer under the control of the processor of the smart armband, and the specific implementation manner is described.
- the description of the prompt corresponding to the context mode is sent in step S210 in the above smart watch embodiment.
- Another method for detecting wearable device drop detection provided by the embodiment of the present invention can determine the scene mode described by the wearer after detecting that the smart armband is detached from the wearer, and issue a prompt to the outside world.
- Still another embodiment of the method for detecting wearable device detachment detection of the embodiment of the present invention may be a smart headband.
- the smart headband includes a processor, an EEG sensor, and a radio frequency circuit.
- the EEG sensor is used to detect the EEG of the wearer's brain.
- Step 1 The EEG sensor collects EEG signal information of the smart headband wearer.
- the EEG sensor can collect the EEG signal information of the wearer in real time or at a time.
- the EEG signal information belongs to the physiological parameter information of the wearer.
- Step 2 The processor determines that the EEG signal abnormality of the wearer is detected according to the EEG sensor, and when the abnormal time exceeds a preset time, determining that the smart headband is detached from the wearer.
- the EEG sensor detects that the wearer's EEG signal is abnormal, and the abnormal time exceeds a preset time, for example, 5 seconds, the processor of the smart headband determines that the smart headband is detached from the wearer.
- Step 3 The processor determines, according to the EEG signal information collected by the brain electrical sensor of the smart headband, the scene mode of the wearer when determining that the smart armband is detached from the wearer.
- the processor determines the scene mode of the wearer according to the EEG signal information collected by the brain electrical sensor of the smart headband when determining that the smart armband is detached from the wearer, specifically:
- Step 3.1 extracting ⁇ wave information from the collected EEG signal information.
- step 3.2 the average value, standard deviation, average energy and the like of the extracted beta wave information of the wearer are analyzed.
- Step 3.3 based on the feature, establish a classifier to identify the situation in which the wearer is located.
- the scene in which the wearer is located includes at least two types:
- the wearer is in an emotional state of panic and a mode in which the wearer is in a state of calm.
- Step 4 The radio frequency circuit of the smart headband is used under the control of the processor of the smart headband to send a prompt corresponding to the scene mode according to the scene mode in which the wearer is located.
- an emergency call may be sent to the preset mobile phone number in the smart headband, or an emergency alert message may be sent; or an alarm device paired with the smart headband or The mobile phone sends an emergency reminder message; it can also be that the smart headband itself issues a prompt, such as the smart headband sounding an alarm sound.
- the smart headband may not issue a prompt message; it may also send a message that the wearer is in a calm mood.
- FIG. 6 is a schematic diagram of a wearable device according to an embodiment of the present invention.
- the wearable device 600 includes:
- a processor 602 a first sensor 604, a second sensor 606, a radio frequency circuit 608, and a power source 610; the processor 602 is communicatively coupled to the first sensor 604, the second sensor 606, and the radio frequency circuit 608; The first sensor 604, the second sensor 606, the processor 602, and the radio frequency circuit 608 are powered.
- the processor 602 is communicatively coupled to the first sensor 604, the second sensor 606, and the radio frequency circuit 608.
- the processor 602 is electrically coupled to the first sensor 604, the second sensor 606, and the radio frequency circuit 608. Connected or connected through an input/output bus, the processor 602 can control and communicate with the first sensor 604, the second sensor 606, and the radio frequency circuit 608.
- the first sensor 604 is configured to collect physiological parameter information of a wearer of the wearable device.
- the processor 602 is configured to determine, according to the first sensor 604, abnormality of the physiological parameter information of the wearer of the wearable device, and determine that the wearable device is detached from the wearer when the abnormal time exceeds a preset time;
- human physiological parameter information includes information such as ECG signal, body temperature, skin resistance, etc.
- the number information includes heart rate, sinus beats and other information.
- the preset time may be set according to different types of the first sensor 604 used, and may be set to a preset time, for example, the preset time is 5 seconds. The specific preset time can be set according to actual needs.
- the second sensor 606 is configured to collect activity information of a wearer of the wearable device
- the processor 602 is further configured to: when the wearable device is detached from the wearer, the physiological parameter information of the wearer of the wearable device collected by the first sensor 604 and the second sensor 106 Determining the activity mode of the wearer of the wearable device, or determining the scene mode in which the wearer is located according to the activity information of the wearer of the wearable device collected by the second sensor 606;
- the processor 602 may refer to the processor 602 at the moment when the wearable device is detached from the wearer, or the processor 602 may The moment after the wearable device is detached from the wearer.
- the activity information of the wearer includes activity status information and activity area information.
- the activity status information refers to the current activity state of the wearer, such as the wearer is running, walking, or the wearer falls;
- the activity area information refers to the current position of the wearer, for example, the wearer is at school, or the wearer is at home. .
- the scene mode is a preset mode of the wearable device, including: a scene mode in which the wearer is normally removed by the wearable device, a scene mode in which the wearer is accidentally dropped by the wearable device, and a scene in which the wearer is in a dangerous state. And one or more of the scenes in which the wearer is in a dangerous state.
- the RF circuit 608 is configured to, under the control of the processor 602, send a prompt corresponding to the scene mode according to the scene mode in which the wearer is located.
- the RF circuit 608 sends a prompt corresponding to the context mode according to the context mode in which the wearer is located, including:
- the RF circuit 608 can issue an emergency call to the preset mobile number in the wearable device, or issue an emergency alert message; the RF circuit 608 can also The alarm or mobile phone paired with the wearable device sends an emergency message.
- the RF circuit 608 can send help information to the handset paired with the wearable device; the RF circuit 608 can also send an alert to the wearer paired with the wearable device. Help information.
- the RF circuit 608 may send a message indicating that the wearable device is unexpectedly detached to the mobile phone paired with the wearable device; The way 608 can also issue an alert to the wearable device that is paired with the wearable device.
- the RF circuit 608 may not issue a prompt message; the RF circuit 608 may also issue a normal removal prompt message.
- the wearable device 600 provided by the embodiment of the present invention includes: a processor 602, a first sensor 604, a second sensor 606, a radio frequency circuit 608, and a power source 610; the processor 602 and the first sensor 604, the second sensor 606
- the power supply unit 610 is configured to provide power to the first sensor 604, the second sensor 606, the processor 602, and the radio frequency circuit 608.
- the wearable device provided by the embodiment of the present invention detects wearableness. After the device is detached from the wearer, the scene pattern described by the wearer can be judged and a prompt is issued to the outside world.
- the first sensor 604 includes one or more of an electrocardiographic sensor, a body temperature sensor, a skin resistance sensor, and a myoelectric sensor.
- the ECG sensor can be used to detect the wearer's ECG signal information, such as heart rate, sinus beat, etc.;
- the body temperature sensor can be used to detect the wearer's body temperature signal information;
- the skin resistance sensor can be used to detect the wearer's skin resistance Signal information;
- the myoelectric sensor can be used to detect the wearer's sEMG information.
- sEMG is the electrical signal that accompanyes the wearer's muscle contraction.
- the second sensor 106 includes one or more of a GPS sensor, a Bluetooth sensor, a three-axis accelerometer sensor, and a gyro sensor.
- the processor 602 may be composed of an integrated circuit (IC), for example, may be composed of a single packaged IC, or may be composed of a plurality of packaged ICs that have the same function or different functions.
- the processor unit may include only a central processing unit (CPU), or a digital signal processor (DSP), and a control chip (for example, a baseband chip) in the communication unit.
- CPU central processing unit
- DSP digital signal processor
- control chip for example, a baseband chip
- the CPU may be a single operation core, and may also include multiple operation cores.
- the radio frequency circuit 608 is configured to receive and transmit information, and the radio frequency circuit 608 can communicate with the network and other devices through wireless communication.
- the wireless communication can use any communication standard or protocol, including but not limited to Global System of Mobile communication (GSM), General Packet Radio Service (GPRS), and code division multiple access ( Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), High Speed Packet Access (HSPA), and Enhanced High Speed Packet Access (High Speed) Packet Access+ (HSPA+), Long Term Evolution (LTE), e-mail, and Short Messaging Service (SMS).
- GSM Global System of Mobile communication
- GPRS General Packet Radio Service
- CDMA Code Division Multiple Access
- WCDMA Wideband Code Division Multiple Access
- HSPA High Speed Packet Access
- HSPA+ High Speed Packet Access+
- LTE Long Term Evolution
- SMS Short Messaging Service
- the wearable device can be a smart watch 700, as shown in FIG.
- the smart watch 700 includes a processor 702, an electrocardiographic sensor 704, a second sensor 706, a radio frequency circuit 708, and a power source 710, wherein the second sensor 706 includes one of a GPS sensor 7061 and a Bluetooth sensor 7062.
- the processor 702 is in communication with the ECG sensor 704, the second sensor 706, and the RF circuit 708; the power source 710 provides power to the processor 702, the ECG sensor 704, the second sensor 706, and the RF circuit 708.
- the ECG sensor 704 is a first sensor of the smart watch 700 for collecting ECG signal information of the physiological parameter information of the wearer of the smart watch 700; the second sensor 206 of the smart watch includes a GPS sensor 7061 and a Bluetooth sensor. One of the 7062.
- the GPS sensor 7061 or the Bluetooth sensor 7062 is used to collect active area information of the wearer's activity information.
- the ECG sensor can collect information such as the wearer's heart rate and sinus heart rate.
- an electrocardiographic sensor is used to collect the sinus heart beat of the wearer as an example for description.
- the processor 702 includes a fall detection unit 7022, an abnormality determining unit 7024, an active area determining unit 7026, and a scene mode determining unit 7028, as shown in FIG. 7a.
- the detachment detecting unit 7022 is configured to detect that the sinus beat information of the wearer of the smart watch is abnormal according to the electrocardiographic sensor, and determine that the smart watch is detached from the wearer when the abnormal time exceeds the preset time.
- the preset time may be 5 seconds.
- the electrocardiographic sensor detects that the sinus beat information of the wearer of the smart watch is abnormal, and the abnormal time exceeds 5 seconds, and the processor determines that the smart watch is detached from the wearer.
- the specific preset time value can be determined according to actual needs.
- the abnormality determining unit 7024 is configured to determine, according to the wearer's sinus beat information collected by the electrocardiographic sensor 704, whether the sinus beat information of the wearer is abnormal. For a specific implementation, refer to the step of how to implement, in step S208, the processor to determine whether the wearer's sinus beat information is abnormal.
- the active area determining unit 7026 is configured to determine, according to the active area information of the wearer collected by the GPS sensor 7061 or the Bluetooth sensor 7062, whether the active area of the wearer is in a preset active area.
- the preset active area is a safe activity area of the wearer. For the specific implementation manner, refer to the division of the preset activity area of the squadron in step S208.
- the scene mode determining unit 7028 is configured to determine a scene mode in which the wearer is located according to the wearer's sinus beat information and the activity area information. For the specific implementation manner, refer to the judgment of the team scene mode in step S208.
- a radio frequency circuit 708 for controlling the wearer under the control of the processor 702 of the smart watch The context mode at which the prompt corresponding to the context mode is sent.
- the smart watch provided by the embodiment of the present invention can determine the scene mode described by the wearer after detecting that the smart watch is detached from the wearer, and issue a prompt to the outside world.
- the wearable device may be a smart bracelet, as shown in FIG. 8.
- the smart bracelet includes a processor 802, a first sensor 804, a second sensor 806, a radio frequency circuit 808, and a power source 810.
- the first sensor 804 includes a body temperature sensor 8041 and a skin resistance sensor 8042; the second sensor 806 includes one of a GPS sensor 8061 and a Bluetooth sensor 8062.
- the processor 802 is in communication with the first sensor 804, the second sensor 806, and the radio frequency circuit 808; the power supply 810 provides power to the processor 802, the first sensor 804, the second sensor 806, and the radio frequency circuit 808.
- the body temperature sensor 8041 is configured to detect body temperature signal information in a wearer's physiological parameter
- the skin resistance sensor 8042 is configured to detect skin resistance signal information in a wearer's physiological parameter
- the second sensor 806 is configured to collect active area information of the wearer's activity information.
- the processor 802 includes a fall detection unit 8022, an abnormality determination unit 8024, an active area determination unit 8206, and a scene mode determination unit 8028, as shown in FIG. 8a.
- the detachment detecting unit 8022 is configured to detect that the body temperature signal information of the wearer of the smart bracelet is abnormal according to the body temperature sensor 8041, and when the abnormal time exceeds the preset time, determine that the smart bracelet is detached from the wearer. For the specific implementation, refer to step S306 above.
- the abnormality determining unit 8024 is configured to determine whether the physiological parameter information of the wearer is abnormal according to the body temperature signal information of the wearer collected by the body temperature sensor 8041 and the skin resistance signal information of the wearer collected by the skin resistance sensor 8042. For the specific implementation, refer to step S308 above.
- the active area determining unit 8026 is configured to determine, according to the active area information of the wearer's activity information collected by the GPS sensor 8061 or the Bluetooth sensor 8062, whether the wearer is in a preset active area. For the specific implementation, refer to step S308 above.
- the scene mode determining unit 8028 is configured to determine a scene mode in which the wearer is located according to the physiological parameter information and the activity area information of the wearer. For the specific implementation, refer to step S308 above.
- the RF circuit 808 is configured to, according to the scene mode of the wearer, send a prompt corresponding to the scene mode under the control of the processor 802 of the smart bracelet.
- the smart wristband provided by the embodiment of the present invention can determine the scene mode described by the wearer after detecting that the smart bracelet is detached from the wearer, and issue a prompt to the outside world.
- the wearable device may be another smart bracelet, as shown in FIG. 9. Shown.
- the smart bracelet includes a processor 902, a body temperature sensor 904, a second sensor 906, a radio frequency circuit 908, and a power source 910.
- the second sensor 906 includes a three-axis accelerometer sensor 9063 and a gyro sensor 9064, and the second sensor 906 further includes one of a GPS sensor 9061 and a Bluetooth sensor 9062.
- the processor 902 is in communication with the body temperature sensor 904, the second sensor 906, and the radio frequency circuit 908; the power supply 910 provides power to the processor 902, the body temperature sensor 804, the second sensor 906, and the radio frequency circuit 908.
- the body temperature sensor 904 is configured to detect body temperature signal information in the wearer's physiological parameters.
- the three-axis accelerometer sensor 9063 is configured to collect acceleration information of the wearer's activity information; the gyroscope sensor 9064 is used to collect angular velocity information of the wearer's activity information; the GSP sensor 9061 or the Bluetooth sensor 9062 is used to collect the wearer's Activity area information of activity information.
- the processor 902 includes a fall detection unit 9022, an abnormality determination unit 9024, an active area determination unit 9026, and a scene mode determination unit 9028, as shown in FIG. 9a.
- the detachment detecting unit 9022 is configured to detect that the body temperature signal information of the wearer of the smart bracelet is abnormal according to the body temperature sensor 904, and determine that the smart bracelet is detached from the wearer when the abnormal time exceeds the preset time.
- the body temperature sensor of the smart bracelet detects that the body temperature signal of the wearer is abnormal, and the abnormal time exceeds a preset time, for example, 3 seconds, or detects that the measured value of the wearer's body temperature signal is lower than a specified body temperature threshold, for example, a specified body temperature threshold.
- the processor of the smart bracelet determines that the smart bracelet is detached from the wearer.
- the abnormality determining unit 9024 is configured to determine whether the wearer's activity state information is abnormal according to the activity state information of the wearer's activity information collected by the three-axis accelerometer sensor 9063 and the gyro sensor 9064. For the specific implementation, refer to step S408 above.
- the active area dividing unit 9026 is configured to use the GPS area 9061 or the active area information of the wearer's activity information collected by the Bluetooth sensor 9062 to determine whether the wearer is in a preset active area. For the specific implementation, refer to step S408 above.
- the scene mode determining unit 9028 is configured to determine a scene mode in which the wearer is located according to the wearer's activity state information and the activity area information. For the specific implementation, refer to step S408 above.
- the RF circuit 908 is configured to send a prompt corresponding to the scene mode according to the scene mode in which the wearer is under the control of the processor 902 of the smart bracelet.
- the scene mode described by the wearer can be judged and a prompt is issued to the outside world.
- the wearable device may be a smart armband, as shown in FIG.
- the smart armband includes a processor 1002, an electromyography sensor 1004, a second sensor 1006, a radio frequency circuit 1008, and a power source 1010.
- the second sensor 1006 includes a three-axis accelerometer sensor 10063 and a gyro sensor 10064, and the second sensor 1006 further includes one of a GPS sensor 10061 and a Bluetooth sensor 10062.
- the processor 1002 is communicatively coupled to the myoelectric sensor 1004, the second sensor 1006, and the radio frequency circuit 1008; the power source 1010 supplies power to the processor 1002, the myoelectric sensor 1004, the second sensor 1006, and the radio frequency circuit 1008.
- the myoelectric sensor 1004 is configured to detect a surface electromyogram signal sEMG of the wearer.
- the three-axis accelerometer sensor 10063 is configured to collect acceleration information of the wearer's activity information; the gyro sensor 10064 is configured to collect angular velocity information of the wearer's activity information; the GSP sensor 10061 or the Bluetooth sensor 10062 is used to collect the wearer's Activity area information of activity information.
- the processor 1002 includes a fall detection unit 10022, an abnormality determination unit 10024, an active area determination unit 10026, and a scene mode determination unit 10028, as shown in FIG. 10a.
- the detachment detecting unit 10022 is configured to detect that the sEMG signal information of the wearer of the smart armband is abnormal according to the myoelectric sensor, and when the abnormal time exceeds the preset time, determine that the smart armband is detached from the wearer.
- the smart armband's myoelectric sensor detects the wearer's sEMG signal abnormality, and the abnormal time exceeds a preset time, for example, 5 seconds, the processor of the smart armband determines that the smart armband is detached from the wearer.
- the abnormality determining unit 10024 is configured to determine whether the wearer's active state is abnormal according to the activity state information of the wearer collected by the myoelectric sensor 1004, the three-axis accelerometer sensor 10063, and the gyro sensor 10064 of the smart armband. For the specific implementation, refer to step S508 above.
- the active area determining unit 10026 is configured to determine, according to the active area information of the wearer collected by the GPS sensor 10061 or the Bluetooth sensor 10062 of the smart armband, whether the wearer is in a preset active area. For the specific implementation, refer to step S508 above.
- the scene mode determining unit 10028 is configured to determine a scene mode in which the wearer is located according to the wearer's activity state information and the activity area information. For the specific implementation, refer to step S508 above.
- the RF circuit 1008 is configured to, under the control of the processor 1002 of the smart armband, send a prompt corresponding to the scene mode according to the scene mode in which the wearer is located.
- the smart armband provided by the embodiment of the present invention can determine the scene mode described by the wearer after detecting that the smart armband is detached from the wearer, and issue a prompt to the outside world.
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Abstract
本发明实施例公开了一种用于可穿戴设备脱落检测的方法和可穿戴设备,该方法包括釆集可穿戴设备的佩戴者的生理参数信息和活动信息;在检测到所述可穿戴设备的佩戴者的生理参数信息异常,并且异常时间超过预设时间时,判断所述可穿戴设备从所述佩戴者身上脱落;在判断所述可穿戴设备从所述佩戴者身上脱落时,根据釆集的所述可穿戴设备的佩戴者的生理参数信息和活动信息,判断所述佩戴者所处的情景模式;根据所述佩戴者所处的情景模式发送与所述情景模式对应的提示。通过该方法,在可穿戴设备脱落时,能够判断佩戴者所述的情景模式,并向外界发出提示。
Description
本发明实施例涉及信息技术领域,尤其涉及一种用于可穿戴设备脱落检测的方法及可穿戴设备。
可穿戴设备以其自身轻巧、紧贴佩戴者身体的特点,成为佩戴者的身体与世界交流的一个适合的载体。可穿戴设备按照产品外型的不同,可以分为手表、手环、眼镜、臂章、挂饰等不同类型。如今,可穿戴设备正在逐渐走入人们的生活,例如通过为儿童佩戴可穿戴设备,家长能够及时掌握孩子的行踪。在某些情况下,可穿戴设备从佩戴者身上脱落表示佩戴者可能处于危险环境,例如不法分子强行摘除儿童的可穿戴设备。在这种情况下,可穿戴设备无法识别佩戴者是否可能存在危险。
发明内容
本发明实施例提供了一种用于可穿戴设备脱落检测的方法及可穿戴设备,在检测到可穿戴设备从佩戴者身上脱落后,能够判断佩戴者所述的情景模式,并向外界发出提示。
第一方面公开了一种用于可穿戴设备脱落检测的方法,所述方法包括:
采集可穿戴设备的佩戴者的生理参数信息和活动信息;
在检测到所述可穿戴设备的佩戴者的生理参数信息异常,并且异常时间超过预设时间时,判断所述可穿戴设备从所述佩戴者身上脱落;
在判断所述可穿戴设备从所述佩戴者身上脱落时,根据采集的所述可穿戴设备的佩戴者的生理参数信息和活动信息,判断所述佩戴者所处的情景模式;
根据所述佩戴者所处的情景模式发送与所述情景模式对应的提示。
结合第一方面,在第一方面的第一种可能的实现方式中,在判断所述可穿戴设备从所述佩戴者身上脱落时,根据采集的所述可穿戴设备的佩戴者的生理参数信息和活动信息,判断所述佩戴者所处的情景模式,具体为:
在判断所述可穿戴设备从所述佩戴者身上脱落时,根据采集的所述可穿戴
设备的佩戴者的生理参数信息的心电信号信息,判断所述佩戴者的心电信号信息是否存在异常;根据采集的所述佩戴者活动信息的活动区域信息,判断所述佩戴者是否处于预设的活动区域;根据采集的所述佩戴者的心电信号信息和活动区域信息判断所述佩戴者所处的情景模式。
结合第一方面,在第一方面的第二种可能的实现方式中,在判断所述可穿戴设备从所述诉佩戴者身上脱落时,根据采集的所述可穿戴设备的佩戴者的生理参数信息和活动信息,判断所述佩戴者所处的情景模式,具体为:
在判断所述可穿戴设备从所述诉佩戴者身上脱落时,根据采集的所述可穿戴设备的佩戴者的生理参数信息的体温信号信息和皮肤电阻信号信息,判断所述佩戴者的生理参数信息是否存在异常;根据采集的所述佩戴者的活动信息的活动区域信息,判断所述佩戴者是否处于预设的活动区域;根据采集的所述佩戴者的体温信号信息、皮肤电阻信息和活动区域信息,判断所述佩戴者所处的情景模式。
结合第一方面,在第一方面的第三种可能的实现方式中,在判断所述可穿戴设备从所述诉佩戴者身上脱落时,根据采集的所述可穿戴设备的佩戴者的生理参数信息和活动信息,判断所述佩戴者所处的情景模式,具体为:
在判断所述可穿戴设备从所诉所述佩戴者身上脱落时,根据采集的所述可穿戴设备的佩戴者的生理参数信息的表面肌电信号sEMG信息、所述可穿戴设备的佩戴者活动信息的加速度信息、所述可穿该设备的佩戴者的活动信息的角速度信息,判断所述佩戴者的活动状态信息是否存在异常;根据采集的所述可穿戴设备的佩戴者的活动信息的活动区域信息,判断所述佩戴者是否位于预设的活动区域;根据采集的所述佩戴者的活动状态信息和活动区域信息,判断所述佩戴者所处的情景模式。
结合第一方面或第一方面的第一种可能的实现方式至第一方面第三种可能实现方式中任一种可能的实现方式,在第一方面的第四种可能的实现方式中,所述情景模式包括:危险状态低的情景模式、危险状态高的情景模式、可穿戴设备正常摘掉的情景模式和可穿戴设备意外脱落的情景模式中的一种或多种。
第二方面公开了一种用于可穿戴设备脱落检测的方法,所述方法包括:
采集可穿戴设备的佩戴者的生理参数信息和活动信息;
在检测到所述可穿戴设备的佩戴者的生理参数信息中断异常,并且中断异常时间超过预设时间时,判断所述可穿戴设备从所述佩戴者身上脱落;
在判断所述可穿戴设备从所述佩戴者身上脱落时,根据采集的所述可穿戴设备的佩戴者的活动信息,判断所述佩戴者所处的情景模式;
根据所述佩戴者所处的情景模式发送执行与所述情景模式对应的提示操作。
结合第二方面,在第二方面的第一种可能的实现方式中,在判断所述可穿戴设备从所诉所述佩戴者身上脱落时,根据采集的所述可穿戴设备的佩戴者的活动信息,判断所述佩戴者所处的情景模式,具体为:
在判断所述可穿戴设备从所述诉佩戴者身上脱落时,根据采集的所述可穿戴设备的佩戴者活动信息的加速度信息和所述可穿该设备的佩戴者的活动信息的角速度信息,判断所述佩戴者的活动状态信息是否存在异常;根据所述佩戴者的活动信息的活动区域信息,判断所述佩戴者是否位于预设的活动区域;根据采集的所述佩戴者的活动状态信息和活动区域信息,判断所述佩戴者所处的情景模式。
结合第二方面或第二方面的第一种可能的实现方式,在第二方面的第二种可能的实现方式中,所述情景模式包括:危险状态低的情景模式、危险状态高的情景模式、可穿戴设备正常摘掉的情景模式和可穿戴设备意外脱落的情景模式中的一种或多种。
第三方面公开了一种可穿戴设备,所述可穿戴设备包括:第一传感器、第二传感器、处理器、电源和射频电路,所述处理器与所述第一传感器、所述第二传感器和所述射频电路通信连接,所述电源给所述第一传感器、所述第二传感器、所述处理器和所述射频电路供电,其中:
所述第一传感器,用于采集所述可穿戴设备的佩戴者的生理参数信息;
所述处理器,用于根据所述第一传感器检测到所述可穿戴设备的佩戴者的生理参数信息中断异常,并且中断异常时间超过预设时间时,判断所述可穿戴设备从所述佩戴者身上脱落;
所述第二传感器,用于采集所述可穿戴设备的佩戴者的活动信息;
所述处理器,在判断所述可穿戴设备从所述佩戴者身上脱落时,还用于根据所述第一传感器采集的所述可穿戴设备的佩戴者的生理参数信息和所述第二传感器采集的所述可穿戴设备的佩戴者的活动信息,判断所述佩戴者所处的情景模式;
射频电路,用于在所述处理器的控制下,根据所述佩戴者所处的情景模式发送执行与所述情景模式对应的提示操作。
结合第三方面,在第三方面的第二种可能的实现方式中,所述第一传感器包括心电传感器、体温传感器、皮肤电阻传感器和肌电传感器中的至少一个。
结合第三方面的第二种可能的实现方式,在第三方面的第二种可能的实现方式中,所述第一传感器为心电传感器时,所述第二传感器包括全球定位***GPS传感器和蓝牙传感器中的一个;所述心电传感器用于采集所述佩戴者的生理参数信息的心电信号信息;
所述处理器,在判断所述可穿戴设备从所述佩戴者身上脱落时,还用于根据所述第一传感器采集的所述可穿戴设备的佩戴者的生理参数信息和所述第二传感器采集的所述可穿戴设备的佩戴者的活动信息,判断所述佩戴者所处的情景模式,具体为:
所述处理器,在判断所述可穿戴设备从所述佩戴者身上脱落时,用于根据所述心电传感器采集的所述佩戴者的生理参数信息的心电信号信息,判断所述佩戴者的心电信号信息是否存在异常;所述处理器还用于根据所述GPS传感器或所述蓝牙传感器采集的所述佩戴者的活动信息的活动区域信息,判断所述佩戴者是否处于的活动信息的预设的活动区域信息;
所述处理器,还用于根据所述佩戴者的心电信号信息的异常情况和活动区域信息,判断所述佩戴者所处的情景模式。
结合第三方面的第二种可能的实现方式,在第三方面的第三种可能的实现方式中,所述第一传感器为体温传感器和所述皮肤电阻传感器时,所述第二传感器包括GPS传感器和蓝牙传感器中的一个;所述体温传感器用于采集所述佩戴者的生理参数信息的体温信号信息;所述皮肤电阻传感器用于采集所述佩戴者的生理参数信息的皮肤电阻信号信息;
所述处理器,在判断所述可穿戴设备从所述佩戴者身上脱落时,还用于根据所述第一传感器采集的所述可穿戴设备的佩戴者的生理参数信息和所述第二传感器采集的所述可穿戴设备的佩戴者的活动信息,判断所述佩戴者所处的情景模式,具体为:
所述处理器,在判断所述可穿戴设备从所述佩戴者身上脱落时,用于根据所述体温传感器采集的所述佩戴者的体温信号信息和所述皮肤电阻传感器采集的所述佩戴者的皮肤电阻信号信息,判断所述佩戴者的生理参数信息是否存在异常;所述处理器还用于根据所述GPS传感器或所述蓝牙传感器采集的所述佩戴者的活动信息的活动区域信息,判断所述佩戴者是否处于预设的活动区域信
息,判断所述佩戴者的活动信息的活动区域信息;
所述处理器,还用于根据所述佩戴者的生理参数信息的异常情况和活动区域信息,判断所述佩戴者所处的情景模式。
结合第三方面的第二种可能的实现方式,在第三方面的第四种可能的实现方式中,其特征在于,所述第一传感器为肌电传感器时,所述第二传感器包括三轴加速度计传感器和陀螺仪传感器,所述第二传感器还包括GPS传感器和蓝牙传感器中的一个;所述肌电传感器用于采集所述佩戴者的生理参数信息的表面肌电信号sEMG信息;
所述处理器,在判断所述可穿戴设备从所述佩戴者身上脱落时,还用于根据所述第一传感器采集的所述可穿戴设备的佩戴者的生理参数信息和所述第二传感器采集的所述可穿戴设备的佩戴者的活动信息,判断所述佩戴者所处的情景模式,具体为:
所述处理器,在判断所述可穿戴设备从所述佩戴者身上脱落时,用于根据所述肌电传感器、所述三轴加速度计传感器和所述陀螺仪传感器采集的信息,判断所述佩戴者的活动信息的活动状态信息;所述处理器还用于根据所述GPS传感器或所述蓝牙传感器采集的所述佩戴者的活动信息的活动区域信息,判断所述佩戴者是否处于的活动信息的预设的活动区域信息;
所述处理器,还用于根据所述佩戴者的活动状态信息和活动区域信息,判断所述佩戴者所处的情景模式。
结合第三方面的第一种可能的实现方式至第三方面第四种可能实现方式中任一种可能的实现方式,在第三方面的第五种可能的实现方式中,其特征在于,所述情景模式包括:危险状态低的情景模式、危险状态高的情景模式、可穿戴设备正常摘掉的情景模式和可穿戴设备意外脱落的情景模式中的一种或多种。
第四方面公开了一种可穿戴设备,所述可穿戴设备包括:第一传感器、第二传感器、处理器、电源和射频电路,所述处理器与所述第一传感器、所述第二传感器和所述射频电路通信连接,所述电源给所述第一传感器、所述第二传感器、所述处理器和所述射频电路供电,其中:
所述第一传感器,用于采集所述可穿戴设备的佩戴者的生理参数信息;
所述处理器,用于根据所述第一传感器检测到所述可穿戴设备的佩戴者的生理参数信息异常,并且异常时间超过预设时间时,判断所述可穿戴设备从所述佩戴者身上脱落;
所述第二传感器,用于采集所述可穿戴设备的佩戴者的活动信息;
所述处理器,在判断所述可穿戴设备从所述佩戴者身上脱落时,还用于根据所述第二传感器采集的所述可穿戴设备的佩戴者的活动信息,判断所述佩戴者所处的情景模式;
射频电路,用于在所述处理器的控制下,根据所述佩戴者所处的情景模式发送与所述情景模式对应的提示。
结合第四方面,在第四方面的第一种可能的实现方式中,所述第一传感器为体温传感器,所述第二传感器包括三轴加速度计传感器和陀螺仪传感器,所述第二传感器还包括GPS传感器和蓝牙传感器中的一个;所述体温传感器用于采集所述佩戴者的生理参数信息的体温信号信息;
所述处理器,在判断所述可穿戴设备从所述佩戴者身上脱落时,还用于根据所述第二传感器采集的所述可穿戴设备的佩戴者的活动信息,判断所述佩戴者所处的情景模式,具体为:
所述处理器,在判断所述可穿戴设备从所述佩戴者身上脱落时,还用于根据所述三轴加速度计传感器和所述陀螺仪传感器采集的所述佩戴者的活动信息的活动状态信息,判断所述佩戴者的活动信息的活动状态信息是否存在异常;所述处理器还用于根据所述GPS传感器或所述蓝牙传感器采集的所述佩戴者的活动信息的活动区域信息,判断所述佩戴者的活动信息的是否处于预设的活动区域信息;
所述处理器,还用于根据所述佩戴者的活动状态信息和活动区域信息,判断所述佩戴者所处的情景模式。
结合第四方面或第四方面的第一种可能的实现方式,在第四方面的第二种可能的实现方式中,所述情景模式包括:危险状态低的情景模式、危险状态高的情景模式、可穿戴设备正常摘掉的情景模式和可穿戴设备意外脱落的情景模式中的一种或多种。
在上述技术方案中,本发明实施例提供的一种用于可穿戴设备脱落检测的方法,通过采集可穿戴设备的佩戴者的生理参数信息和活动信息;在检测到所述可穿戴设备的佩戴者的生理参数信息异常,并且异常时间超过预设时间时,判断所述可穿戴设备从所述佩戴者身上脱落;在判断所述可穿戴设备从所述佩戴者身上脱落时,根据采集的所述可穿戴设备的佩戴者的生理参数信息和活动信息,判断所述佩戴者所处的情景模式;根据所述佩戴者所处的情景模式发送
与所述情景模式对应的提示,能够在检测到可穿戴设备从佩戴者身上脱落后,判断佩戴者所述的情景模式,并向外界发出提示。
为了更清楚地说明本发明实施例中的技术方案,下面将对实施例描述中所需要使用的附图作简单地介绍,显而易见地,下面描述中的附图仅仅是本发明的一些实施例,对于本领域普通技术人员来讲,在不付出创造性劳动的前提下,还可以根据这些附图获得其它的附图。
图1是本发明实施例提供的一种用于可穿戴设备脱落检测的方法的示意图;
图2是本发明实施例提供的又一种用于可穿戴设备脱落检测的方法的示意图;
图3是本发明实施例提供的再一种用于可穿戴设备脱落检测的方法的示意图;
图4是本发明实施例提供的又一种用于可穿戴设备脱落检测的方法的示意图;
图5是本发明实施例提供的再一种用于可穿戴设备脱落检测的方法的示意图;
图6是本发明实施例提供的一种可穿戴设备的结构示意图;
图7是本发明实施例提供的又一种可穿戴设备的结构示意图;
图7a是本发明实施例提供的又一种可穿戴设备的结构示意图;
图8是本发明实施例提供的再一种可穿戴设备的结构示意图;
图8a是本发明实施例提供的再一种可穿戴设备的结构示意图;
图9是本发明实施例提供的又一种可穿戴设备的结构示意图;
图9a是本发明实施例提供的又一种可穿戴设备的结构示意图;
图10是本发明实施例提供的再一种可穿戴设备的结构示意图;
图10a是本发明实施例提供的再一种可穿戴设备的结构示意图。
为使本发明实施例的目的、技术方案和优点更加清楚,下面将结合本发明实施例中的附图,对本发明实施例中的技术方案进行清楚地描述,显然,所描述的实施例是本发明一部分实施例,而不是全部的实施例。基于本发明中的实施例,本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例,都属于本发明保护的范围。
本发明实施例的可穿戴设备(Wearable Devices)包括手表(watch)、手环(wristband)、眼镜(glass)、臂章(armband)、以及融合到服装、鞋子、袜子、头盔、帽子等电子设备。
人情绪的波动能够影响人的脉搏、体温等生理参数,例如,精神紧张和情绪激动可以使人的脉搏跳动加快和体温升高。因此可以通过监测人的某些生理参数,判断人情绪的波动情况。人情绪的波动在一定程度上能够反映出人所处环境的变化。例如,佩戴者出现心跳加速、体温升高等情况,表明佩戴者可能处于危险的环境。
图1给出了本发明实施例提供的一种用于可穿戴设备脱落检测的方法的示意图,该方法100的执行主体可以为可穿戴设备,该方法100包括以下步骤:
S102:采集可穿戴设备的佩戴者的生理参数信息和活动信息。
其中,其中,人的生理参数信息包括心电信号、体温、皮肤电阻、表面肌电信号(Surface Electromyography,简称sEMG)、脑电图信号(Electroencephalograph,简称EEG)等信息,心电信号信息包括心率、窦性心搏等信息。活动信息包括活动状态信息和活动区域信息。
其中,心电信号信息可以通过心电传感器实时或定时采集;体温信号信息可以通过体温传感器实时或定时采集;皮肤电阻信息可以通过皮肤电阻传感器实时或定时采集;sEMG信号信息可以通过肌电传感器实时或定时采集。通过对佩戴者的sEMG信号信息的分析,能够确定佩戴者的活动状态信息的手臂动作和/或手势动作信息。活动状态信息的加速度信息可以通过三轴加速度计传感器实时或定时采集;活动状态信息的角速度信息可以通过陀螺仪传感器实时或定时采集;活动区域信息可以通过全球定位***(Global Position System,简称GPS)传感器或蓝牙(Bluetooth)传感器实时或定时采集。该蓝牙传感器是指一种支持短距离无线通信技术的设备,能够在包括移动电话、掌上电脑、无线耳机、笔记本电脑、可穿戴设备等之间进行无线信息交换。该蓝牙传感器具体可以为一蓝牙芯片。
S104:检测到该可穿戴设备的佩戴者的生理参数信息异常,并且异常时间超过预设时间时,判断该可穿戴设备从该佩戴者身上脱落。
其中,生理参数信息可以通过不同的传感器采集。该预设时间可以根据传感器类型的不同,设置不同的预设时间。也可以设置为统一的预设时间,例如该预设时间为5秒钟。具体的预设时间,可以根据实际需要设定。异常包括采集的信号中断的情况。
S106:在判断该可穿戴设备从所述佩戴者身上脱落时,根据采集的该可穿戴设备的佩戴者的生理参数信息和活动信息,或根据采集的该可穿戴设备的佩戴者的活动信息,判断该佩戴者所处的情景模式。
其中,佩戴者处于的情景模式包括:危险状态低的情景模式、危险状态高的情景模式、可穿戴设备正常摘掉的情景模式和可穿戴设备意外脱落的情景模式中的一种或多种。
S108:根据该佩戴者所处的情景模式发送与该情景模式对应的提示。
其中,发送与该情景模式对应的提示具体为:
(1)、如果佩戴者处于危险状态高的情景模式,可以向可穿戴设备内预设的手机号码发出紧急呼叫,或发出紧急提示信息;也可以向与可穿戴设备配对的报警器或手机发出紧急提示信息;也可以是该可穿戴设备本身发出提示,如该可穿戴设备发出报警声音。
(2)、如果佩戴者处于危险状态低的情景模式,可以向与可穿戴设备配对的手机发出求助信息;也可以向与可穿戴设备配对的报警器发出求助信息;也可以是该可穿戴设备本身发出提示,如该可穿戴设备发出报警声音。
(3)、如果佩戴者处于可穿戴设备意外脱落的情景模式,可以向与可穿戴设备配对的手机发出可穿戴设备意外脱落提示信息;也可以向与可穿戴设备配对的报警器发出可穿戴设备意外脱落提示信息;也可以是该可穿戴设备本身发出提示,如该可穿戴设备发出报警声音。
(4)、如果佩戴者处于可穿戴设备正常摘掉的情景模式,该可穿戴设备可以不发出提示信息;也可以发出正常摘掉提示信息。
本发明实施例提供的一种用于可穿戴设备脱落检测的方法,通过采集可穿戴设备的佩戴者的生理参数信息和活动信息;在检测到该可穿戴设备的佩戴者的生理参数信息异常,并且异常时间超过预设时间时,判断该可穿戴设备从该佩戴者身上脱落;在判断该可穿戴设备从所述佩戴者身上脱落时,根据采集的
该可穿戴设备的佩戴者的生理参数信息和活动信息,或根据采集的该可穿戴设备的佩戴者的活动信息,判断该佩戴者所处的情景模式;根据该佩戴者所处的情景模式发送与该情景模式对应的提示,能够在检测到可穿戴设备从佩戴者身上脱落后,能够判断佩戴者所述的情景模式,并向外界发出提示。
图2给出了本发明实施例的一种用于可穿戴设备脱落检测的方法200的示意图,该方法200的执行设备可以是一智能手表,该智能手表包括处理器、心电传感器、GPS传感器和蓝牙传感器中的一个、射频电路。该心电传感器用于采集该智能手表的佩戴者的生理参数信息的心电信号信息;该GPS传感器或蓝牙传感器用于采集佩戴者的活动信息的活动区域信息。心电传感器可以采集佩戴者的心率、窦性心搏等信息。本发明实施例以心电传感器采集佩戴者的窦性心搏为例进行说明。
本发明实施例提供的用于可穿戴设备脱落检测的方法200,在检测到其从佩戴者身上脱落后,能够判断佩戴者所述的情景模式,并向外界发出提示,具体步骤为:
S202:心电传感器用于采集智能手表的佩戴者的窦性心搏。
心电传感器可以实时或定时采集佩戴者的心电信号信息的窦性心搏信息。心电信号信息属于佩戴者的生理参数信息。
S204:GPS传感器或蓝牙传感器用于采集该智能手表的佩戴者的活动区域信息。
GPS传感器或蓝牙传感器可以实时或定时采集该智能手表的佩戴者的活动区域信息。佩戴者的活动区域信息指佩戴者当前所处的位置,比如,佩戴者在学校,或者佩戴者在家中等。
S206:处理器,根据心电传感器检测到智能手表的佩戴者的心电信号信息异常,并且异常时间超过预设时间时,判断智能手表从佩戴者身上脱落。
该预设时间可以是5秒钟,例如,处理器检测到智能手表的佩戴者的心电信号信息异常,并且异常时间超过5秒钟,处理器判断该智能手表从该佩戴者身上脱落。具体的预设时间值可以根据实际需要确定。异常包括采集的信号中断。例如,心电信号信息中断超过5秒钟。
S208:处理器,在判断该智能手表从该佩戴者身上脱落时,根据该心电传感器采集的该佩戴者的窦性心搏信息,判断该佩戴者的窦性心搏信息是否存在异常;该处理器还根据GPS传感器或蓝牙传感器采集的佩戴者的活动区域信息,判断该佩戴者的活动区域是否处于预设的活动区域;处理器根据该佩戴者的窦
性心搏信息和活动区域信息,判断该佩戴者所处的情景模式。
其中,该预设的活动区域可以为该佩戴者的安全活动区域。
S210:该智能手表的射频电路,在该智能手表的处理器的控制下,用于根据该佩戴者所处的情景模式,发送与该情景模式对应的提示。
其中,步骤S208中,处理器判断该佩戴者的窦性心搏信息是否存在异常,包括以下步骤:
步骤2081:处理器分析该智能手表从佩戴者身上脱落前指定时间段内,心电传感器检测到的窦性心搏信息。
其中,该指定时间可以是10分钟。具体的时间段值可以根据实际需要设定。
步骤2082:将上述指定时间段分成预先设定的M个时间段,M为正整数。例如将上述指定时间段分为2个时间段,第一个时间段为第1至5分钟;第二个时间段为为第6至10分钟。计算第一个时间段内每相邻两个窦性心搏的时间间隔,再计算第一个时间段内上述时间间隔的平均值,记为计算第二个时间段内每相邻两个窦性心搏的时间间隔,再计算第二个时间段内上述时间间隔的平均值,记为具体的时间段的个数M,可以根据实际需要设定。
步骤2083:分别计算上述M个时间段内窦性心搏的时间间隔的标准差(Standard Deviation,简称SD)。标准差的计算公式为:
其中,N为对应时间段内检测到的窦性心搏的次数,ti是对应时间段内第i个相邻两个窦性心搏的时间间隔,是对应时间段内窦性心搏的时间间隔的平均值。该第一个时间段内窦性心搏的时间间隔的标准差记为x1,该第二个时间段内窦性心搏的时间间隔的标准差记为x2。
步骤2084:判断不同时间段内窦性心搏的时间间隔的平均值的变化率是否超过指定的平均值阈值ε1。该指定的平均值阈值ε1可以是0.15。具体的指定的平均值阈值ε1可以根据实际需要设定。判断公式为:
步骤2085:判断不同时间段内窦性心搏的时间间隔的标准差的变化率是否超过指定的标准差阈值ε2。该指定的标准差阈值ε2可以是0.1。具体的指定的标
准差阈值ε2可以根据实际需要设定。判断公式为:
如果窦性心搏的时间间隔的平均值的变化率和标准差的变化率均超过指定的阈值,则认为佩戴者的心率变异性(Heart Rate Variability,简称HRV)发生了显著变化,即佩戴者的窦性心搏信息存在异常。
其中,步骤S208中,处理器判断该佩戴者的活动区域是否处于预设的活动区域,具体为:
处理器根据GPS传感器或者蓝牙传感器采集的佩戴者的活动区域信息,判断佩戴者的活动区域是否处于预设的活动区域。该预设的活动区域为佩戴者的安全活动区域。
在下述情况下,佩戴者处于预设活动区域。
(1)、当前时间为上学时间,GPS传感器定位结果为佩戴者所处位置为学校;
(2)、当前时间为放学时间或佩戴者去上学的路上的时间,GPS传感器定位结果为佩戴者处于预设的放学或上学路径内;
(3)、当前时间,GPS定位结果为佩戴者位于家中;
(4)、将佩戴者的可穿戴设备与监督者的手机或报警器配对通信连接,当前时间,通过与该手机或该报警器的蓝牙传感器定位结果为,该佩戴者和该监督者的距离不超过指定距离,例如该指定距离可以是10米。
在下述情况下,佩戴者处于非预设活动区域:
(1)、当前时间为上学时间,GPS传感器定位结果为佩戴者所处位置为学校之外的区域;
(2)、当前时间为放学时间或佩戴者去上学的路上的时间,GPS传感器定位结果为佩戴者处于预设的放学或上学路径之外的区域;
(3)、将佩戴者的可穿戴设备与监督者的手机或报警器配对连接,当前时间,通过与该手机或该报警器的蓝牙传感器定位结果为,该佩戴者和该监督者的距离超过指定距离,例如该指定距离可以是10米。
其中,步骤S208中,处理器根据该佩戴者的窦性心搏信息和活动区域信息,判断该佩戴者所处的情景模式,具体为:
(1)、该可穿戴设备的处理器通过分析佩戴者的心电信号信息,发现指定时间段内,窦性心搏的时间间隔的平均值的变化率为0.19,大于指定的平均值阈值ε1=0.15;窦性心搏的时间间隔的标准差的变化率为0.14,大于指定的标准差阈值ε2=0.1,因此该智能手表的处理器判断佩戴者的HRV发生显著变化。GPS传感器定位结果显示,该智能手表脱落时佩戴者当前所处的位置与当前时间对应的安全活动区域不匹配,例如智能手表脱落的时间为上学时间,当前时间对应的安全活动区域为学校,GPS传感器定位结果显示佩戴者所处的位置不在学校内,因此佩戴者的活动区域出现异常。该智能手表的处理器结合佩戴者的HRV信息和活动区域信息,判断出佩戴者当前所处的情景模式为“佩戴者处于危险状态高的情景模式”。
(2)、该可穿戴设备的处理器通过分析佩戴者的心电信号信息,发现指定时间段内,窦性心搏的时间间隔的平均值的变化率为0.19,大于指定的平均值阈值ε1=0.15;窦性心搏的时间间隔的标准差的变化率为0.14,大于指定的标准差阈值ε2=0.1,因此该可穿戴设备的处理器判断佩戴者的HRV发生显著变化。GPS传感器定位结果显示,该智能手表脱落时佩戴者当前所处的位置与当前时间对应的安全活动区域匹配,例如该智能手表脱落的时间为上学时间,当前时间对应的安全活动区域为学校,GPS传感器定位结果显示佩戴者所处位置在学校内,因此佩戴者的活动区域正常。该可穿戴设备的处理器结合佩戴者的HRV信息和活动区域信息,判断出佩戴者当前所处的情景模式为“佩戴者处于危险状态低的情景模式”。
(3)、该可穿戴设备的处理器分析佩戴者的心电信号信息,发现指定时间段内,窦性心搏的时间间隔的平均值的变化率为0.09,小于指定的平均值阈值ε1=0.15;窦性心搏的时间间隔的标准差的变化率为0.04,小于指定的标准差阈值ε2=0.1,因此该可穿戴设备的处理器判断佩戴者的HRV未发生显著变化。GPS传感器定位结果显示,该智能手表脱落时佩戴者当前所处的位置与当前时间对应的安全活动区域不匹配,例如智能手表脱落的时间为放学时间,当前时间对应的安全活动区域为预设的放学回家路径,GPS传感器定位结果显示佩戴者所处的位置不在该放学回家路径内,因此佩戴者的活动区域出现异常。该可穿戴设备的处理器结合佩戴者的HRV信息和活动区域信息,判断出佩戴者当前所处的情景模式为“佩戴者处于可穿戴设备意外脱落的情景模式”。
(4)、该可穿戴设备的处理器分析佩戴者的心电信号信息,发现指定时间段内,窦性心搏的时间间隔的平均值的变化率为0.09,小于指定的平均值阈值ε1=0.15;窦性心搏的时间间隔的标准差的变化率为0.04,小于指定的标准差
阈值ε2=0.1,因此认为佩戴者的HRV未发生显著变化。GPS传感器定位结果显示,该智能手表脱落时佩戴者当前所处的位置与当前时间对应的安全活动区域匹配,例如智能手表脱落的时间为晚上休息时间,当前时间对应的安全活动区域为家里,GPS传感器定位结果显示佩戴者所处的位置在家里,因此佩戴者的活动区域正常。该可穿戴设备的处理器结合佩戴者的HRV信息和活动区域信息,判断出佩戴者当前所处的情景模式为“佩戴者处于可穿戴设备正常摘掉的情景模式”。
可选的,处理器根据该佩戴者的窦性心搏信息和活动区域信息,判断该佩戴者所处的情景模式,还可以为:
(1)、该可穿戴设备的处理器通过分析佩戴者的心电信号信息,发现指定时间段内,窦性心搏的时间间隔的平均值的变化率为0.19,大于指定的平均值阈值ε1=0.15;窦性心搏的时间间隔的标准差的变化率为0.14,大于指定的标准差阈值ε2=0.1,因此该智能手表的处理器判断佩戴者的HRV发生显著变化。GPS传感器定位结果显示,该智能手表脱落时佩戴者当前所处的位置与当前时间对应的安全活动区域不匹配,例如智能手表脱落的时间为上学时间,当前时间对应的安全活动区域为学校,GPS传感器定位结果显示佩戴者所处的位置不在学校内,因此佩戴者的活动区域出现异常。该智能手表的处理器结合佩戴者的HRV信息和活动区域信息,判断出佩戴者当前所处的情景模式为“佩戴者处于危险状态高的情景模式”。
(2)、该可穿戴设备的处理器通过分析佩戴者的心电信号信息,发现指定时间段内,窦性心搏的时间间隔的平均值的变化率为0.19,大于指定的平均值阈值ε1=0.15;窦性心搏的时间间隔的标准差的变化率为0.14,大于指定的标准差阈值ε2=0.1,因此该可穿戴设备的处理器判断佩戴者的HRV发生显著变化。GPS传感器定位结果显示,该智能手表脱落时佩戴者当前所处的位置与当前时间对应的安全活动区域匹配,例如该智能手表脱落的时间为上学时间,当前时间对应的安全活动区域为学校,GPS传感器定位结果显示佩戴者所处位置在学校内,因此佩戴者的活动区域正常。该可穿戴设备的处理器结合佩戴者的HRV信息和活动区域信息,判断出佩戴者当前所处的情景模式为“佩戴者处于危险状态低的情景模式”。
(3)、该可穿戴设备的处理器分析佩戴者的心电信号信息,发现指定时间段内,窦性心搏的时间间隔的平均值的变化率为0.09,小于指定的平均值阈值ε1=0.15;窦性心搏的时间间隔的标准差的变化率为0.04,小于指定的标准差
阈值ε2=0.1,因此该可穿戴设备的处理器判断佩戴者的HRV未发生显著变化。GPS传感器定位结果显示,该智能手表脱落时佩戴者当前所处的位置与当前时间对应的安全活动区域不匹配,例如智能手表脱落的时间为放学时间,当前时间对应的安全活动区域为预设的放学回家路径,GPS传感器定位结果显示佩戴者所处的位置不在该放学回家路径内,因此佩戴者的活动区域出现异常。该可穿戴设备的处理器结合佩戴者的HRV信息和活动区域信息,判断出佩戴者当前所处的情景模式为“佩戴者处于危险状态低的情景模式”。
(4)、该可穿戴设备的处理器分析佩戴者的心电信号信息,发现指定时间段内,窦性心搏的时间间隔的平均值的变化率为0.09,小于指定的平均值阈值ε1=0.15;窦性心搏的时间间隔的标准差的变化率为0.04,小于指定的标准差阈值ε2=0.1,因此认为佩戴者的HRV未发生显著变化。GPS传感器定位结果显示,该智能手表脱落时佩戴者当前所处的位置与当前时间对应的安全活动区域匹配,例如智能手表脱落的时间为晚上休息时间,当前时间对应的安全活动区域为家里,GPS传感器定位结果显示佩戴者所处的位置在家里,因此佩戴者的活动区域正常。该可穿戴设备的处理器结合佩戴者的HRV信息和活动区域信息,判断出佩戴者当前所处的情景模式为“佩戴者处于可穿戴设备意外脱落的情景模式”。
其中,步骤S210中,该智能手表的射频电路,在该智能手表的处理器的控制下,用于根据该佩戴者所处的情景模式,发送与该情景模式对应的提示,具体为:
(1)、如果佩戴者处于危险状态高的情景模式,该智能手表的射频电路可以向该可穿戴设备内预设的手机号码发出紧急呼叫,或发出紧急提示信息;该智能手表的射频电路也可以向与该可穿戴设备配对的报警器发出紧急提示信息,或该智能手表的射频电路可以向与该可穿戴设备配对的手机发出求助信息;该智能手表本身也可以发出提示,如该智能手表发出报警声音。
(2)、如果佩戴者处于危险状态低的情景模式,该智能手表的射频电路可以向与该可穿戴设备配对的手机发出求助信息;该智能手表的射频电路也可以向与该可穿戴设备配对的报警器发出求助信息;该智能手表本身也可以发出提示,如该智能手表发出报警声音。
(3)、如果佩戴者处于可穿戴设备意外脱落的情景模式,该智能手表的射频电路可以向与该可穿戴设备配对的手机发出可穿戴设备意外脱落提示信息;该智能手表的射频电路也可以向与该可穿戴设备配对的报警器发出可穿戴设备意
外脱落提示信息;该智能手表本身也可以发出提示,如该智能手表发出报警声音。
(4)、如果佩戴者处于可穿戴设备正常摘掉的情景模式,该智能手表的射频电路可以不发出提示信息;该智能手表的射频电路也可以发出正常摘掉提示信息。
若采用心电传感器采集佩戴者的心率信息,以判断佩戴者的生理参数信息是否存在异常,方案与心电传感器采集佩戴者的窦性心搏同理。
通过本发明实施例提供的用于可穿戴设备脱落检测的方法,在检测到该智能手表从佩戴者身上脱落后,能够判断佩戴者所述的情景模式,并向外界发出提示。
图3给出了本发明实施例的又一用于可穿戴设备脱落检测的方法300,该方法300的执行设备可以是一智能手环,下面以智能手环为例,对本发明实施例提供的又一用于可穿戴设备脱落检测的方法进行说明。
该智能手环包括处理器、第一传感器、第二传感器和射频电路。该智能手环的第一传感器包括体温传感器和皮肤电阻传感器,该体温传感器用于检测佩戴者生理参数中的体温信号信息,该皮肤电阻传感器用于检测佩戴者生理参数中的皮肤电阻信号信息;第二传感器包括GPS传感器和蓝牙传感器中的一个,该第二传感器用于采集佩戴者的活动信息的活动区域信息。本发明实施例提供的智能手环,在检测到智能手环从佩戴者身上脱落后,能够判断佩戴者所述的情景模式,并向外界发出提示,具体步骤为:
S302:体温传感器用于采集智能手环的佩戴者的体温信号信息;皮肤电阻传感器用于采集该智能手环的佩戴者的皮肤电阻信息。
体温传感器可以实时或定时采集智能手环的佩戴者的体温信号信息;皮肤电阻传感器可以实时或定时采集该智能手环的佩戴者的皮肤电阻信息。其中,体温信号信息和皮肤电阻信号信息属于佩戴者的生理参数信息。
S304:GPS传感器或蓝牙传感器用于采集该智能手环的佩戴者的活动区域信息。
GPS传感器或蓝牙传感器可以实时或定时采集智能手环的佩戴者的活动区域信息。佩戴者的活动区域信息指佩戴者当前所处的位置,比如,佩戴者在学校,或者佩戴者在家中等。
S306:处理器,根据体温传感器检测到智能手环的佩戴者的体温信号信息
异常,并且异常时间超过预设时间时,判断智能手环从佩戴者身上脱落。
处理器判断智能手环从佩戴者的身上脱落可以是通过体温传感器检测到佩戴者的体温信号异常,且异常时间超过预设时间,例如3秒钟,或者检测到佩戴者的体温信号的测量值低于指定体温阈值,例如指定体温阈值为26℃;处理器判断智能手环从佩戴者的身上脱落还可以是通过该处皮肤电阻传感器检测到皮肤电阻信号异常,且异常时间超过预设时间,例如3秒钟,则该处理器判断该智能手环从佩戴者身上脱落。
S308:处理器,在判断该智能手环从该佩戴者身上脱落时,根据该体温传感器采集的该佩戴者的体温信号信息和该皮肤电阻传感器采集的该佩戴者的皮肤电阻信号信息,判断该佩戴者的生理参数信息是否存在异常;该处理器还根据该GPS传感器或该蓝牙传感器采集的该佩戴者的活动信息的活动区域信息,判断该佩戴者是否处于预设的活动区域;处理器根据该佩戴者的生理参数信息和活动区域信息,判断该佩戴者所处的情景模式。
其中,该预设的活动区域为该佩戴者的安全活动区域。
S310:该智能手环的射频电路,在该智能手环的处理器的控制下,用于根据该佩戴者所处的情景模式,发送与该情景模式对应的提示。
其中,步骤S308中,处理器判断该佩戴者的生理参数信息是否存在异常,包括以下步骤:
步骤3081:该智能手环的处理器分析该智能手环从佩戴者身上脱落前指定时间段内,体温传感器采集的佩戴者的体温信号。该指定时间段时长可以是2分钟,具体的时长可以根据实际需要确定。例如,该智能手环的处理器分析该智能手环从佩戴者身上脱落前2分钟内,体温传感器采集到的体温信号。记第1分钟内的体温信号的平均值为t1,记第2分钟内的体温信号的平均值为t2,如果|t1-t2|<Δt,则认为佩戴者的体温信号出现异常。本发明实施例中,Δt可以取0.5℃。Δt的取值可以根据实际需要确定。
步骤3082:该智能手环的处理器分析该智能手环从佩戴者身上脱落前指定时间段内,皮肤电阻传感器采集的佩戴者的皮肤电阻信号。该指定时间段时长可以是2分钟,具体的时间段时长以根据实际需要确定。例如,该智能手环的处理器分析该智能手环从佩戴者身上脱落前2分钟内,皮肤电阻传感器采集到的皮肤电阻信号。该智能手环的处理器计算该指定时间段内检测到的皮肤电阻信号的平均值Ω和平均标准方差ΔΩ。首先将该指定时间段划分为多个时间窗口,
该时间窗口的宽度为预设值。例如,该时间窗口的宽度预设值为10秒钟。然后计算每个时间窗口内采集到的皮肤电阻信号的平均值。如果连续三个时间窗口内的皮肤电阻信号的平均值均在区间范围[Ω-3×ΔΩ,Ω+3×ΔΩ]之外,则该智能手环的处理器判断该佩戴者的皮肤电阻信号出现异常。
如果该佩戴者的体温信号和皮肤电阻信号均出现异常波动,则认为佩戴者的生理参数信息出现异常波动。
其中,步骤S308中,处理器判断该佩戴者的活动区域是否处于预设的活动区域,具体参见上述智能手表实施例中,对步骤S208中智能手表的佩戴者的预设活动区域的划分。
其中,步骤S308中,处理器根据该佩戴者的生理参数信息和活动区域信息,判断该佩戴者所处的情景模式,情景模式的识别结果如表1情景模式识别结果所示:
表1情景模式识别结果
情景模式的又一识别结果如表2情景模式的又一识别结果所示:
表2情景模式的又一识别结果
其中,步骤S310中,该智能手环的射频电路,在该智能手环的处理器的控制下,用于根据该佩戴者所处的情景模式,发送与该情景模式对应的提示,具体实现方式,参见上文智能手表实施例中对步骤S210中发送与给情景模式对应的提示的描述。
通过本发明实施例提供的方法300,在检测到该智能手环从佩戴者身上脱落后,能够判断佩戴者所述的情景模式,并向外界发出提示,
图4给出了本发明实施例的再一用于可穿戴设备脱落检测的方法400,该方法400的执行设备可以是又一智能手环。
该智能手环包括处理器、第一传感器、第二传感器和射频电路。该智能手环的第一传感器为体温传感器,该体温传感器用于检测佩戴者生理参数中的体温信号信息;第二传感器包括三轴加速度计传感器和陀螺仪传感器,该第二传感器还包括GPS传感器和蓝牙传感器中的一个。该第二传感器中的三轴加速度计传感器用于采集佩戴者的活动状态信息的加速度信息;陀螺仪传感器用于采集佩戴者的活动状态信息的角速度信息;该第二传感器中的GPS传感器或蓝牙传感器用于检测佩戴者的活动信息的活动区域信息。本发明实施例提供的方法400,在检测到智能手环从佩戴者身上脱落后,能够判断佩戴者所述的情景模式,并向外界发出提示,具体步骤为:
S402:体温传感器用于采集智能手环的佩戴者的体温信号信息。
体温传感器可以实时或定时采集智能手环的佩戴者的体温信号信息。其中,体温信号信息属于佩戴者的生理参数信息。
S404:处理器,根据体温传感器检测到智能手环的佩戴者的体温信号信息异常,并且异常时间超过预设时间时,判断智能手环从佩戴者身上脱落。
该智能手环的体温传感器检测到佩戴者的体温信号异常,且异常时间超过预设时间,例如3秒钟,或者检测到佩戴者的体温信号的测量值低于指定体温阈值,例如指定体温阈值为26℃,则该智能手环的处理器判断该智能手环从佩戴者身上脱落。
S406:三轴加速度计传感器用于采集佩戴者的加速度信息;陀螺仪传感器用于采集佩戴者的角速度信息;GPS传感器或蓝牙传感器用于采集佩戴者的活动区域信息。
其中,佩戴者的活动信息包括活动状态信息和活动区域信息。佩戴者的活动状态信息包括由三轴加速度计传感器确定的佩戴者的加速度信息和由陀螺仪传感器确定的佩戴者的角速度信息。
三轴加速度计传感器可以实时或定时采集佩戴者的加速度信息;陀螺仪传感器可以实时或定时采集佩戴者的角速度信息;GPS传感器或蓝牙传感器可以实时或定时采集佩戴者的活动区域信息。
S408:处理器,在判断该智能手环从该佩戴者身上脱落时,根据该三轴加速度计传感器和该陀螺仪传感器采集的该佩戴者的活动信息的活动状态信息,
判断该佩戴者的活动状态信息是否存在异常;该处理器还根据该GPS传感器或该蓝牙传感器采集的该佩戴者的活动信息的活动区域信息,判断该佩戴者是否处于预设的活动区域;处理器根据该佩戴者的活动状态信息和活动区域信息,判断该佩戴者所处的情景模式。
其中,该预设的活动区域为该佩戴者的安全活动区域。
S410:该智能手环的射频电路,在该智能手环的处理器的控制下,用于根据该佩戴者所处的情景模式,发送与该情景模式对应的提示。
其中,步骤S408中,处理器根据该三轴加速度计传感器和陀螺仪传感器采集的该佩戴者的活动信息的活动状态信息,判断该佩戴者的活动状态信息是否存在异常,具体步骤为:
步骤4081:该智能手环的处理器分析智能手环脱落前指定时间段内,三轴加速度计传感器采集的佩戴者的加速度信息。该指定时间段的时长可以是1分钟,具体的时间段时长可以根据实际需要确定。根据该三轴加速度计传感器采集的每个轴上的加速度测量值,计算合加速度。计算公式为:
其中,ax为三轴加速计传感器在x轴方向的加速度测量值,ay为三轴加速计传感器在y轴方向的加速度测量值,az为三轴加速计传感器在z轴方向的加速度测量值,a为合加速度。
步骤4082:比较合加速度a与指定加速度阈值εa,判断合加速度a是否大于指定加速度阈值εa。该指定加速度阈值可以是εa=4.6m/s2,具体的指定加速度阈值大小可以根据实际需要设定。
步骤4083:计算佩戴者的智能手环的倾斜角度θ,并与指定倾斜角阈值εθ比较,判断智能手环的倾斜角度θ是否大于指定倾斜角阈值εθ。该指定倾斜角阈值可以是εθ=50°。其中,倾斜角度θ的计算公式为:
其中,a为步骤4081中计算得到的合加速度;g为重力加速度,g=9.81m/s2。
步骤4084:该智能手环的处理器分析该智能手环从佩戴者身上脱落前指定时间段内陀螺仪传感器采集到的角速度信号。通过分析角速度信号信息,判断该智能手环是否存在周期性振荡。
步骤4085:综合步骤4083和步骤4084的分析结果,将佩戴者的活动状态分为活动状态正常和活动状态异常,结果如表3活动状态判断结果所示:
表3活动状态判断结果
步骤4086:该智能手环的处理器通过分析GPS传感器或者蓝牙传感器采集的信息判断佩戴者是否处于预设的活动区域,具体的预设活动区域的划分参见上述智能手表实施例中,对步骤S208中智能手表的佩戴者的预设活动区域的划分。其中,该预设的活动区域为佩戴者的安全活动区域。
其中,步骤S408中,处理器根据该佩戴者的活动状态信息和活动区域信息,判断该佩戴者所处的情景模式,情景模式的识别结果如表4情景模式识别结果所示:
表4情景模式识别结果
情景模式的又一识别结果如表5情景模式的又一识别结果所示:
表5情景模式的又一识别结果
其中,步骤S410中,该智能手环的射频电路,在该智能手环的处理器的控制下,用于根据该佩戴者所处的情景模式,发送与该情景模式对应的提示,具体实现方式,参见上文智能手表实施例中对步骤S210中发送与给情景模式对应的提示的描述。
通过本发明实施例提供的又一用于可穿戴设备脱落检测的方法400,在检测
到该智能手环从佩戴者身上脱落后,能够判断佩戴者所述的情景模式,并向外界发出提示,
图5给出了本发明实施例的又一用于可穿戴设备脱落检测的方法500,该方法500的执行设备可以是智能臂章。下面以智能臂章为例,对本发明实施例提供的又一用于可穿戴设备脱落检测的方法进行说明。
该智能臂章包括处理器、第一传感器、第二传感器和射频电路。该智能臂章的第一传感器为肌电传感器,用于检测佩戴者的表面肌电信号sEMG。第二传感器包括三轴加速度计传感器和陀螺仪传感器,该第二传感器还包括GPS传感器和蓝牙传感器中的一个。该第二传感器中的三轴加速度计传感器和陀螺仪传感器用于采集佩戴者的活动信息的活动状态信息;该第二传感器中的GPS传感器和蓝牙传感器用于检测佩戴者的活动信息的活动区域信息。
利用sEMG信号可识别佩戴者的手势动作的生理学基础是,肢体的特定关节的运动由其对应的肌肉群控制。由于sEMG信号不但能反映关节的伸屈状态和伸屈强度,还能反映人做出手势过程中手的形状、位置、朝向和运动信息,此外,利用从对应肌肉群采集到的sEMG信号,还能识别包括上肢前臂动作、肘关节动作、腕关节动作和手指动作在内的手势动作。其中,手指动作又包括单指动作和组合手指动作。例如,腕关节动作包括,伸腕动作、屈腕动作、正掌动作和反掌动作等。
本发明实施例提供的用于可穿戴设备脱落检测的方法500,在检测到智能臂章从佩戴者身上脱落后,能够判断佩戴者所述的情景模式,并向外界发出提示,具体步骤为:
S502:肌电传感器采集智能臂章的佩戴者的sEMG信号信息。
肌电传感器可以实时或定时采集智能臂章的佩戴者的sEMG信号信息。其中,sEMG信号信息属于佩戴者的生理参数信息。
S504:处理器,根据肌电传感器检测到智能臂章的佩戴者的sEMG信号信息异常,并且异常时间超过预设时间时,判断智能臂章从佩戴者身上脱落。
该智能臂章的肌电传感器检测到佩戴者的sEMG信号异常,且异常时间超过预设时间,例如5秒钟,则该智能臂章的处理器判断该智能臂章从佩戴者身上脱落。
S506:三轴加速度计传感器用于采集佩戴者的加速度信息;陀螺仪传感器
用于采集佩戴者的角速度信息;GPS传感器或蓝牙传感器用于采集佩戴者的活动区域信息。
其中,佩戴者的活动信息包括活动状态信息和活动区域信息。佩戴者的活动状态信息包括由肌电传感器确定的佩戴者的手势动作和/或手臂动作信息、由三轴加速度计传感器确定的佩戴者的加速度信息和由陀螺仪传感器确定的佩戴者的角速度信息。
三轴加速度计传感器可以实时或定时采集佩戴者的加速度信息;陀螺仪传感器可以实时或定时采集佩戴者的角速度信息;GPS传感器或蓝牙传感器可以实时或定时采集佩戴者的活动区域信息。
S508:处理器,在判断该智能臂章从该佩戴者身上脱落时,根据该智能臂章的肌电传感器、三轴加速度计传感器和陀螺仪传感器采集的佩戴者的活动状态信息,判断该佩戴者的活动状态是否存在异常;该处理器还根据该智能臂章的GPS传感器或蓝牙传感器采集的佩戴者的活动区域信息,判断该佩戴者是否处于预设的活动区域;处理器根据该佩戴者的活动状态信息和活动区域信息,判断该佩戴者所处的情景模式。
其中,该预设的活动区域为该佩戴者的安全活动区域。
S510:该智能臂章的射频电路,在该智能臂章的处理器的控制下,用于根据该佩戴者所处的情景模式,发送与该情景模式对应的提示。
其中,步骤S508中,处理器,根据该智能臂章的肌电传感器、三轴加速度计传感器和陀螺仪传感器采集的佩戴者的活动信息的活动状态信息,判断该佩戴者的活动状态是否存在异常,具体为:
该智能臂章的处理器通过对肌电传感器、三轴加速度计传感器和陀螺仪传感器采集的该佩戴者的信号信息进行模式识别,将模式识别结果与该智能臂章预设的手臂动作和手势动作进行比较,以判断二者是否匹配。其中,预设的手臂动作和手势动作对应着佩戴者不同的活动状态。如果该智能臂章的处理器判断佩戴者当前的手臂动作和/或手势动作与预设的手臂动作和手势动作匹配成功,则可以判断到佩戴者当前的活动状态。例如,该智能臂章的处理器通过对肌电传感器、三轴加速度计传感器和陀螺仪传感器采集的信号进行分析,发现佩戴者当前的手臂动作和/或手势动作可能存在异常,处理器通过对上述采集到的信号进行模式识别,并将模式识别结果与预设的手臂动作和手势动作对应的数据作比较,判断到佩戴者当前的手臂动作和/或手势动作为曲腕向后摆臂,则智能
臂章的处理器判断佩戴者当前的活动状态异常。
其中,步骤S508中,处理器根据该智能臂章的GPS传感器或该蓝牙传感器采集的该佩戴者的活动信息的活动区域信息,判断该佩戴者是否处于预设的活动区域的具体实现方式,参见上文智能手表实施例中,对步骤S208中智能手表的佩戴者的预设活动区域的划分。其中,该预设的活动区域为佩戴者的安全活动区域。
其中,步骤S508中,处理器根据该佩戴者的活动状态信息和活动区域信息,判断该佩戴者所处的情景模式,情景模式的识别结果如表4和表5所示。
其中,步骤S510中,该智能臂章的射频电路,在该智能臂章的处理器的控制下,用于根据该佩戴者所处的情景模式,发送与该情景模式对应的提示,具体实现方式,参见上文智能手表实施例中对步骤S210中发送与给情景模式对应的提示的描述。
本发明实施例提供的又一用于可穿戴设备脱落检测的方法,在检测到智能臂章从佩戴者身上脱落后,能够判断佩戴者所述的情景模式,并向外界发出提示。
本发明实施例的又一用于可穿戴设备脱落检测的方法的执行主体可以是一智能头箍。该智能头箍包括处理器、脑电传感器、和射频电路。该脑电传感器用于检测佩戴者的脑电信号EEG。
步骤1,该脑电传感器采集该智能头箍佩戴者的EEG信号信息。
脑电传感器可以实时或定时采集佩戴者的EEG信号信息。其中,EEG信号信息属于佩戴者的生理参数信息。
步骤2,处理器,根据脑电传感器检测到佩戴者的EEG信号异常,并且异常时间超过预设时间时,判断该智能头箍从佩戴者身上脱落。
该脑电传感器检测到佩戴者的EEG信号异常,且异常时间超过预设时间,例如5秒钟,则该智能头箍的处理器判断该智能头箍从佩戴者身上脱落。
步骤3,处理器,在判断该智能臂章从该佩戴者身上脱落时,根据该智能头箍的脑电传感器采集的EEG信号信息,判断该佩戴者所处的情景模式。
其中,处理器,在判断该智能臂章从该佩戴者身上脱落时,根据该智能头箍的脑电传感器采集的EEG信号信息,判断该佩戴者所处的情景模式,具体为:
步骤3.1,从采集的脑电信号信息中提取β波信息。
其中,在佩戴者情绪紧张、焦虑不安、惊慌恐惧时,β波在脑电信号中会出现的频率会急剧上升的情况。
步骤3.2,分析提取的佩戴者的β波信息的平均值、标准差、平均能量等特征。
步骤3.3,根据所述特征,建立分类器,识别用佩戴者所处的情景。
其中,所述佩戴者所处的情景至少包括两种:
佩戴者处于情绪状态为恐慌的情景模式和佩戴者处于情绪状态为平静的情景模式。
步骤4,该智能头箍的射频电路,在该智能头箍的处理器的控制下,用于根据该佩戴者所处的情景模式,发送与该情景模式对应的提示。
其中,若佩戴者处于情绪状态为恐慌的情景模式,则可以向该智能头箍内预设的手机号码发出紧急呼叫,或发出紧急提示信息;也可以向与该智能头箍配对的报警器或手机发出紧急提示信息;也可以是该智能头箍本身发出提示,如该智能头箍发出报警声音。
若佩戴者处于情绪状态为平静的情景模式,该智能头箍可以不发出提示信息;也可以发出佩戴者处于情绪平静的提示信息。
图6给出了本发明实施例提供的一种可穿戴设备的示意图,该可穿戴设备600包括:
处理器602、第一传感器604、第二传感器606、射频电路608和电源610;该处理器602与该第一传感器604、该第二传感器606和该射频电路608通信连接;该电源610给该第一传感器604、该第二传感器606、该处理器602和该射频电路608供电。
其中,该处理器602与该第一传感器604、该第二传感器606和该射频电路608通信连接是指,该处理器602与该第一传感器604、该第二传感器606和该射频电路608电连接或者通过输入输出总线连接,该处理器602能够控制该第一传感器604、该第二传感器606和该射频电路608,并与之通信。
该第一传感器604,用于采集该可穿戴设备的佩戴者的生理参数信息。
该处理器602,用于根据该第一传感器604检测到该可穿戴设备的佩戴者的生理参数信息异常,并且异常时间超过预设时间时,判断该可穿戴设备从该佩戴者身上脱落;
其中,人的生理参数信息包括心电信号、体温、皮肤电阻等信息,心电信
号信息包括心率、窦性心搏等信息。该预设时间可以根据使用的第一传感器604类型的不同,设置不同的预设时间,,也可以设置为统一的预设时间,比如该预设时间为5秒钟。具体的预设时间,可以根据实际需要设定。
该第二传感器606,用于采集该可穿戴设备的佩戴者的活动信息;
该处理器602,在判断该可穿戴设备从该佩戴者身上脱落时,还用于根据该第一传感器604采集的该可穿戴设备的佩戴者的生理参数信息和该第二传感器106采集的该可穿戴设备的佩戴者的活动信息,或者根据该第二传感器606采集的该可穿戴设备的佩戴者的活动信息,确定该佩戴者所处的情景模式;
其中,该处理器602在判断该可穿戴设备从该佩戴者身上脱落时,可以是指处理器602在该可穿戴设备从该佩戴者身上脱落的时刻,也可以是指处理器602在该可穿戴设备从该佩戴者身上脱落后的时刻。
其中,佩戴者的活动信息包括活动状态信息和活动区域信息。活动状态信息指佩戴者当前的活动状态,比如佩戴者在跑步,在走路,或者佩戴者跌倒等;活动区域信息指佩戴者当前所处的位置,比如,佩戴者在学校,或者佩戴者在家中等。
该情景模式是该可穿戴设备预设的情景模式,包括:佩戴者处于可穿戴设备正常摘掉的情景模式、佩戴者处于可穿戴设备意外脱落的情景模式、佩戴者处于危险状态低的情景模式和佩戴者处于危险状态高的情景模式中的一种或多种。
射频电路608,用于在该处理器602的控制下,根据该佩戴者所处的情景模式发送与该情景模式对应的提示。
其中,该射频电路608据该佩戴者所处的情景模式发送与该情景模式对应的提示包括:
(1)、如果佩戴者处于危险状态高的情景模式,该射频电路608可以向该可穿戴设备内预设的手机号码发出紧急呼叫,或发出紧急提示信息;该射频电路608也可以向与该可穿戴设备配对的报警器或手机发出紧急提示信息。
(2)、如果佩戴者处于危险状态低的情景模式,该射频电路608可以向与该可穿戴设备配对的手机发出求助信息;该射频电路608也可以向与该可穿戴设备配对的报警器发出求助信息。
(3)、如果佩戴者处于可穿戴设备意外脱落的情景模式,该射频电路608可以向与该可穿戴设备配对的手机发出可穿戴设备意外脱落提示信息;该射频电
路608也可以向与该可穿戴设备配对的报警器发出可穿戴设备意外脱落提示信息。
(4)、如果佩戴者处于可穿戴设备正常摘掉的情景模式,该射频电路608可以不发出提示信息;该射频电路608也可以发出正常摘掉提示信息。
本发明实施例提供的可穿戴设备600,包括:处理器602、第一传感器604、第二传感器606、射频电路608和电源610;该处理器602与该第一传感器604、该第二传感器606和该射频电路608通信连接;该电源610给该第一传感器604、该第二传感器606、该处理器602和该射频电路608供电,本发明实施例提供的可穿戴设备,在检测到可穿戴设备从佩戴者身上脱落后,能够判断佩戴者所述的情景模式,并向外界发出提示。
具体的,该第一传感器604包括心电传感器、体温传感器、皮肤电阻传感器和肌电传感器中的一个或多个。该心电传感器可以用于检测佩戴者的心电信号信息,比如心率、窦性心搏等;该体温传感器可以用于检测佩戴者的体温信号信息;该皮肤电阻传感器可以用于检测佩戴者的皮肤电阻信号信息;该肌电传感器可以用于检测佩戴者的sEMG信息。sEMG是佩戴者肌肉收缩时伴随的电信号。该第二传感器106包括:GPS传感器、蓝牙传感器、三轴加速度计传感器和陀螺仪传感器中的一个或多个。
具体的,该处理器602可以由集成电路(Integrated Circuit,简称IC)组成,例如可以由单颗封装的IC所组成,也可以由连接多颗相同功能或不同功能的封装IC而组成。举例来说,处理器单元可以仅包括中央处理器(Central Processing Unit,简称CPU),也可以是数字信号处理器(Digital Signal Processor,简称DSP)、及通信单元中的控制芯片(例如基带芯片)的组合。在本发明实施方式中,CPU可以是单运算核心,也可以包括多运算核心。
具体的,该射频电路608射频电路用于接收和发送信息,该射频电路608可以通过无线通信与网络和其他设备通信。该无线通信可以使用任一通信标准或协议,包括但不限于全球移动通讯***(Global System of Mobile communication,简称GSM)、通用分组无线服务(General Packet Radio Service,简称GPRS)、码分多址(Code Division Multiple Access,简称CDMA)、宽带码分多址(Wideband Code Division Multiple Access,简称WCDMA)、高速分组接入技术(High Speed Packet Access,简称HSPA)、增强型高速分组接入技术(High Speed Packet Access+,简称HSPA+)、长期演进(Long Term Evolution,简称LTE)、电子邮件、短消息服务(Short Messaging Service,简称SMS)等。
在本发明提供的一个实施例中,该可穿戴设备可以是智能手表700,如图2所示。该智能手表700包括处理器702、心电传感器704、第二传感器706、射频电路708和电源710,其中第二传感器706包括GPS传感器7061和蓝牙传感器7062中的一个。处理器702与心电传感器704、第二传感器706和射频电路708通信连接;电源710给处理器702、心电传感器704、第二传感器706和射频电路708供电。
该心电传感器704为该智能手表700的第一传感器,用于采集该智能手表700的佩戴者的生理参数信息的心电信号信息;该智能手表的第二传感器206包括GPS传感器7061和蓝牙传感器7062中的一个。GPS传感器7061或蓝牙传感器7062用于采集佩戴者的活动信息的活动区域信息。其中,心电传感器可以采集佩戴者的心率、窦性心搏等信息。本发明实施例以心电传感器采集佩戴者的窦性心搏为例进行说明。
处理器702包括脱落检测单元7022、异常判断单元7024、活动区域判断单元7026、情景模式判断单元7028,如图7a所示。
脱落检测单元7022,用于根据心电传感器检测到智能手表的佩戴者的窦性心搏信息异常,并且异常时间超过预设时间时,判断智能手表从佩戴者身上脱落。
该预设时间可以是5秒钟,例如,心电传感器检测到智能手表的佩戴者的窦性心搏信息异常,并且异常时间超过5秒钟,处理器判断该智能手表从该佩戴者身上脱落。具体的预设时间值可以根据实际需要确定。
异常判断单元7024,用于根据该心电传感器704采集的该佩戴者的窦性心搏信息,判断该佩戴者的窦性心搏信息是否存在异常。具体实现方式,参见步骤S208中如何实现处理器判断该佩戴者的窦性心搏信息是否存在异常的步骤。
活动区域判断单元7026,用于根据GPS传感器7061或蓝牙传感器7062采集的佩戴者的活动区域信息,判断该佩戴者的活动区域是否处于预设的活动区域。其中,该预设的活动区域为该佩戴者的安全活动区域。具体实现方式,参见步骤S208中队预设活动区域的划分。
情景模式判断单元7028,用于根据该佩戴者的窦性心搏信息和活动区域信息,判断该佩戴者所处的情景模式。具体实现方式,参见步骤S208中队情景模式的判断。
射频电路708,用于在该智能手表的处理器702的控制下,根据该佩戴者所
处的情景模式,发送与该情景模式对应的提示。
通过本发明实施例提供的智能手表,在检测到该智能手表从佩戴者身上脱落后,能够判断佩戴者所述的情景模式,并向外界发出提示。
在本发明实施例提供的又一实施例中,该可穿戴设备可以是智能手环,如图8所示。该智能手环包括处理器802、第一传感器804、第二传感器806、射频电路808和电源810。其中,第一传感器804包括体温传感器8041和皮肤电阻传感器8042;第二传感器806包括GPS传感器8061和蓝牙传感器8062中的一个。处理器802与第一传感器804、第二传感器806和射频电路808通信连接;电源810给处理器802、第一传感器804、第二传感器806和射频电路808供电。
该体温传感器8041用于检测佩戴者生理参数中的体温信号信息,该皮肤电阻传感8042器用于检测佩戴者生理参数中的皮肤电阻信号信息。该第二传感器806用于采集佩戴者的活动信息的活动区域信息。
处理器802包括脱落检测单元8022、异常判断单元8024、活动区域判断单元8206和情景模式判断单元8028,如图8a所示。
脱落检测单元8022,用于根据体温传感器8041检测到智能手环的佩戴者的体温信号信息异常,并且异常时间超过预设时间时,判断智能手环从佩戴者身上脱落。具体实现方式参见上文步骤S306。
异常判断单元8024,用于根据该体温传感器8041采集的该佩戴者的体温信号信息和该皮肤电阻传感器8042采集的该佩戴者的皮肤电阻信号信息,判断该佩戴者的生理参数信息是否存在异常。具体实现方式参见上文步骤S308。
活动区判断单元8026,用于据该GPS传感器8061或该蓝牙传感器8062采集的该佩戴者的活动信息的活动区域信息,判断该佩戴者是否处于预设的活动区域。具体实现方式参见上文步骤S308。
情景模式判断单元8028,用于根据该佩戴者的生理参数信息和活动区域信息,判断该佩戴者所处的情景模式。具体实现方式参见上文步骤S308。
射频电路808,用于,在该智能手环的处理器802的控制下,根据该佩戴者所处的情景模式,发送与该情景模式对应的提示。
通过本发明实施例提供的智能手环,在检测到该智能手环从佩戴者身上脱落后,能够判断佩戴者所述的情景模式,并向外界发出提示。
在本发明提供的再一实施例中,该可穿戴设备可以是又一智能手环,如图9
所示。该智能手环包括处理器902、体温传感器904、第二传感器906、射频电路908和电源910。其中,第二传感器906包括三轴加速度计传感器9063和陀螺仪传感器9064,第二传感器906还包括GPS传感器9061和蓝牙传感器9062中的一个。处理器902与体温传感器904、第二传感器906和射频电路908通信连接;电源910给处理器902、体温传感器804、第二传感器906和射频电路908供电。
其中,该体温传感器904用于检测佩戴者生理参数中的体温信号信息。该三轴加速度计传感器9063用于采集佩戴者的活动信息的加速度信息;该陀螺仪传感器9064用于采集佩戴者的活动信息的角速度信息;该GSP传感器9061或蓝牙传感器9062用于采集佩戴者的活动信息的活动区域信息。
处理器902包括脱落检测单元9022、异常判断单元9024、活动区域判断单元9026和情景模式判断单元9028,如图9a所示。
脱落检测单元9022,用于根据体温传感器904检测到智能手环的佩戴者的体温信号信息异常,并且异常时间超过预设时间时,判断智能手环从佩戴者身上脱落。
该智能手环的体温传感器检测到佩戴者的体温信号异常,且异常时间超过预设时间,例如3秒钟,或者检测到佩戴者的体温信号的测量值低于指定体温阈值,例如指定体温阈值为26℃,则该智能手环的处理器判断该智能手环从佩戴者身上脱落。
异常判断单元9024,用于根据该三轴加速度计传感器9063和该陀螺仪传感器9064采集的该佩戴者的活动信息的活动状态信息,判断该佩戴者的活动状态信息是否存在异常。具体实现方式参见上文步骤S408。
活动区域划分单元9026,用于GPS传感器9061或该蓝牙传感器9062采集的该佩戴者的活动信息的活动区域信息,判断该佩戴者是否处于预设的活动区域。具体实现方式参见上文步骤S408。
情景模式判断单元9028,用于根据该佩戴者的活动状态信息和活动区域信息,判断该佩戴者所处的情景模式。具体实现方式参见上文步骤S408。
射频电路908,在该智能手环的处理器902的控制下,用于根据该佩戴者所处的情景模式,发送与该情景模式对应的提示。
通过本发明实施例提供的又一智能手环,在检测到该智能手环从佩戴者身上脱落后,能够判断佩戴者所述的情景模式,并向外界发出提示。
在本发明实施例提供的又一实施例中,该可穿该设备可以是一智能臂章,如图10所示。该智能臂章包括处理器1002、肌电传感器1004、第二传感器1006、射频电路1008和电源1010。其中,第二传感器1006包括三轴加速度计传感器10063和陀螺仪传感器10064,第二传感器1006还包括GPS传感器10061和蓝牙传感器10062中的一个。处理器1002与肌电传感器1004、第二传感器1006和射频电路1008通信连接;电源1010给处理器1002、肌电传感器1004、第二传感器1006和射频电路1008供电。
其中,肌电传感器1004,用于检测佩戴者的表面肌电信号sEMG。该三轴加速度计传感器10063用于采集佩戴者的活动信息的加速度信息;该陀螺仪传感器10064用于采集佩戴者的活动信息的角速度信息;该GSP传感器10061或蓝牙传感器10062用于采集佩戴者的活动信息的活动区域信息。
处理器1002包括脱落检测单元10022、异常判断单元10024、活动区域判断单元10026和情景模式判断单元10028,如图10a所示。
脱落检测单元10022,用于根据肌电传感器检测到智能臂章的佩戴者的sEMG信号信息异常,并且异常时间超过预设时间时,判断智能臂章从佩戴者身上脱落。
该智能臂章的肌电传感器检测到佩戴者的sEMG信号异常,且异常时间超过预设时间,例如5秒钟,则该智能臂章的处理器判断该智能臂章从佩戴者身上脱落。
异常判断单元10024,用于根据该智能臂章的肌电传感器1004、三轴加速度计传感器10063和陀螺仪传感器10064采集的佩戴者的活动状态信息,判断该佩戴者的活动状态是否存在异常。具体实现方式参见上文步骤S508。
活动区域判断单元10026,用于根据该智能臂章的GPS传感器10061或蓝牙传感器10062采集的佩戴者的活动区域信息,判断该佩戴者是否处于预设的活动区域。具体实现方式参见上文步骤S508。
情景模式判断单元10028,用于根据该佩戴者的活动状态信息和活动区域信息,判断该佩戴者所处的情景模式。具体实现方式参见上文步骤S508。
射频电路1008,用于在该智能臂章的处理器1002的控制下,用于根据该佩戴者所处的情景模式,发送与该情景模式对应的提示。
本发明实施例提供的智能臂章,在检测到智能臂章从佩戴者身上脱落后,能够判断佩戴者所述的情景模式,并向外界发出提示。
最后应说明的是:以上实施例仅用以示例性说明本发明的技术方案,而非对其限制;尽管参照前述实施例对本发明及本发明带来的有益效果进行了详细的说明,本领域的普通技术人员应当理解:其依然可以对前述各实施例所记载的技术方案进行修改,或者对其中部分技术特征进行等同替换;而这些修改或者替换,并不使相应技术方案的本质脱离本发明权利要求的范围。
Claims (17)
- 一种用于可穿戴设备脱落检测的方法,其特征在于,所述方法包括:采集所述可穿戴设备的佩戴者的生理参数信息和活动信息;在检测到所述可穿戴设备的佩戴者的生理参数信息异常,并且异常时间超过预设时间时,判断所述可穿戴设备从所述佩戴者身上脱落;在判断所述可穿戴设备从所述佩戴者身上脱落时,根据采集的所述可穿戴设备的佩戴者的生理参数信息和活动信息,判断所述佩戴者所处的情景模式;根据所述佩戴者所处的情景模式发送与所述情景模式对应的提示。
- 根据权利要求1所述的方法,其特征在于,在判断所述可穿戴设备从所述佩戴者身上脱落时,根据采集的所述可穿戴设备的佩戴者的生理参数信息和活动信息,判断所述佩戴者所处的情景模式,具体为:在判断所述可穿戴设备从所述佩戴者身上脱落时,根据采集的所述可穿戴设备的佩戴者的生理参数信息的心电信号信息,判断所述佩戴者的心电信号信息是否存在异常;根据采集的所述佩戴者活动信息的活动区域信息,判断所述佩戴者是否处于预设的活动区域;根据采集的所述佩戴者的心电信号信息和活动区域信息判断所述佩戴者所处的情景模式。
- 根据权利要求1所述的方法,其特征在于,在判断所述可穿戴设备从所述佩戴者身上脱落时,根据采集的所述可穿戴设备的佩戴者的生理参数信息和活动信息,判断所述佩戴者所处的情景模式,具体为:在判断所述可穿戴设备从所述佩戴者身上脱落时,根据采集的所述可穿戴设备的佩戴者的生理参数信息的体温信号信息和皮肤电阻信号信息,判断所述佩戴者的生理参数信息是否存在异常;根据采集的所述佩戴者的活动信息的活动区域信息,判断所述佩戴者是否处于预设的活动区域;根据采集的所述佩戴者的体温信号信息、皮肤电阻信息和活动区域信息,判断所述佩戴者所处的情景模式。
- 根据权利要求1所述的方法,其特征在于,在判断所述可穿戴设备从所述佩戴者身上脱落时,根据采集的所述可穿戴设备的佩戴者的生理参数信息和活动信息,判断所述佩戴者所处的情景模式,具体为:在判断所述可穿戴设备从所述佩戴者身上脱落时,根据采集的所述可穿戴设备的佩戴者的生理参数信息的表面肌电信号sEMG信息、所述可穿戴设备的 佩戴者活动信息的加速度信息、所述可穿该设备的佩戴者的活动信息的角速度信息,判断所述佩戴者的活动状态信息是否存在异常;根据采集的所述可穿戴设备的佩戴者的活动信息的活动区域信息,判断所述佩戴者是否位于预设的活动区域;根据采集的所述佩戴者的活动状态信息和活动区域信息,判断所述佩戴者所处的情景模式。
- 根据权利要求1至4任一项所述的方法,其特征在于,所述情景模式包括:危险状态低的情景模式、危险状态高的情景模式、可穿戴设备正常摘掉的情景模式和可穿戴设备意外脱落的情景模式中的一种或多种。
- 一种用于可穿戴设备脱落检测的方法,其特征在于,所述方法包括:采集可穿戴设备的佩戴者的生理参数信息和活动信息;在检测到所述可穿戴设备的佩戴者的生理参数信息异常,并且异常时间超过预设时间时,判断所述可穿戴设备从所述佩戴者身上脱落;在判断所述可穿戴设备从所述佩戴者身上脱落时,根据采集的所述可穿戴设备的佩戴者的活动信息,判断所述佩戴者所处的情景模式;根据所述佩戴者所处的情景模式发送与所述情景模式对应的提示。
- 根据权利要求6所述的方法,其特征在于,在判断所述可穿戴设备从所述佩戴者身上脱落时,根据采集的所述可穿戴设备的佩戴者的活动信息,判断所述佩戴者所处的情景模式,具体为:在判断所述可穿戴设备从所述佩戴者身上脱落时,根据采集的所述可穿戴设备的佩戴者活动信息的加速度信息和所述可穿该设备的佩戴者的活动信息的角速度信息,判断所述佩戴者的活动状态信息是否存在异常;根据所述佩戴者的活动信息的活动区域信息,判断所述佩戴者是否位于预设的活动区域;根据采集的所述佩戴者的活动状态信息和活动区域信息,判断所述佩戴者所处的情景模式。
- 根据权利要求6或7所述的方法,其特征在于,所述情景模式包括:危险状态低的情景模式、危险状态高的情景模式、可穿戴设备正常摘掉的情景模式和可穿戴设备意外脱落的情景模式中的一种或多种。
- 一种可穿戴设备,其特征在于,所述可穿戴设备包括:第一传感器、第二传感器、处理器、电源和射频电路,所述处理器与所述第一传感器、所述第二传感器和所述射频电路通信连接,所述电源给所述第一传感器、所述第二传感器、所述处理器和所述射频电路供电,其中:所述第一传感器,用于采集所述可穿戴设备的佩戴者的生理参数信息;所述处理器,用于根据所述第一传感器检测到所述可穿戴设备的佩戴者的生理参数信息异常,并且异常时间超过预设时间时,判断所述可穿戴设备从所述佩戴者身上脱落;所述第二传感器,用于采集所述可穿戴设备的佩戴者的活动信息;所述处理器,在判断所述可穿戴设备从所述佩戴者身上脱落时,还用于根据所述第一传感器采集的所述可穿戴设备的佩戴者的生理参数信息和所述第二传感器采集的所述可穿戴设备的佩戴者的活动信息,判断所述佩戴者所处的情景模式;射频电路,用于在所述处理器的控制下,根据所述佩戴者所处的情景模式发送与所述情景模式对应的提示。
- 根据权利要求9所述的可穿戴设备,其特征在于,所述第一传感器包括心电传感器、体温传感器、皮肤电阻传感器和肌电传感器中的至少一个。
- 根据权利要求10所述的可穿戴设备,其特征在于,所述第一传感器为所述心电传感器时,所述第二传感器包括全球定位***GPS传感器和蓝牙传感器中的一个;所述心电传感器用于采集所述佩戴者的生理参数信息的心电信号信息;所述处理器,在判断所述可穿戴设备从所述佩戴者身上脱落时,还用于根据所述第一传感器采集的所述可穿戴设备的佩戴者的生理参数信息和所述第二传感器采集的所述可穿戴设备的佩戴者的活动信息,判断所述佩戴者所处的情景模式,具体为:所述处理器,在判断所述可穿戴设备从所述佩戴者身上脱落时,用于根据所述心电传感器采集的所述佩戴者的生理参数信息的心电信号信息,判断所述佩戴者的心电信号信息是否存在异常;所述处理器还用于根据所述GPS传感器或所述蓝牙传感器采集的所述佩戴者的活动信息的活动区域信息,判断所述佩戴者是否处于预设的活动区域;所述处理器,还用于根据所述佩戴者的心电信号信息和活动区域信息,判断所述佩戴者所处的情景模式。
- 根据权利要求10所述的可穿戴设备,其特征在于,所述第一传感器包括所述体温传感器和所述皮肤电阻传感器时,所述第二传感器包括GPS传感器和蓝牙传感器中的一个;所述体温传感器用于采集所述佩戴者的生理参数信息的体温信号信息;所述皮肤电阻传感器用于采集所述佩戴者的生理参数信息的皮肤电阻信号信息;所述处理器,在判断所述可穿戴设备从所述佩戴者身上脱落时,还用于根据所述第一传感器采集的所述可穿戴设备的佩戴者的生理参数信息和所述第二传感器采集的所述可穿戴设备的佩戴者的活动信息,判断所述佩戴者所处的情景模式,具体为:所述处理器,在判断所述可穿戴设备从所述佩戴者身上脱落时,用于根据所述体温传感器采集的所述佩戴者的体温信号信息和所述皮肤电阻传感器采集的所述佩戴者的皮肤电阻信号信息,判断所述佩戴者的生理参数信息是否存在异常;所述处理器还用于根据所述GPS传感器或所述蓝牙传感器采集的所述佩戴者的活动信息的活动区域信息,判断所述佩戴者是否处于预设的活动区域;所述处理器,还用于根据所述佩戴者的生理参数信息和活动区域信息,判断所述佩戴者所处的情景模式。
- 根据权利要求10所述的可穿戴设备,其特征在于,所述第一传感器包括所述肌电传感器时,所述第二传感器包括三轴加速度计传感器和陀螺仪传感器,所述第二传感器还包括GPS传感器和蓝牙传感器中的一个;所述肌电传感器用于采集所述佩戴者的生理参数信息的表面肌电信号sEMG信息;所述处理器,在判断所述可穿戴设备从所述佩戴者身上脱落时,还用于根据所述第一传感器采集的所述可穿戴设备的佩戴者的生理参数信息和所述第二传感器采集的所述可穿戴设备的佩戴者的活动信息,判断所述佩戴者所处的情景模式,具体为:所述处理器,在判断所述可穿戴设备从所述佩戴者身上脱落时,用于根据所述肌电传感器、所述三轴加速度计传感器和所述陀螺仪传感器采集的信息,判断所述佩戴者的活动信息的活动状态信息;所述处理器还用于根据所述GPS传感器或所述蓝牙传感器采集的所述佩戴者的活动信息的活动区域信息,判断所述佩戴者是否处于预设的活动区域;所述处理器,还用于根据所述佩戴者的活动状态信息和活动区域信息,判断所述佩戴者所处的情景模式。
- 根据权利要求10至13任一项所述的可穿戴设备,其特征在于,所述情景模式包括:危险状态低的情景模式、危险状态高的情景模式、可穿戴设备正常摘掉的情景模式和可穿戴设备意外脱落的情景模式中的一种或多种。
- 一种可穿戴设备,其特征在于,所述可穿戴设备包括:第一传感器、第二传感器、处理器、电源和射频电路,所述处理器与所述第一传感器、所述第二传感器和所述射频电路通信连接,所述电源给所述第一传感器、所述第二传感器、所述处理器和所述射频电路供电,其中:所述第一传感器,用于采集所述可穿戴设备的佩戴者的生理参数信息;所述处理器,用于根据所述第一传感器检测到所述可穿戴设备的佩戴者的生理参数信息异常,并且异常时间超过预设时间时,判断所述可穿戴设备从所述佩戴者身上脱落;所述第二传感器,用于采集所述可穿戴设备的佩戴者的活动信息;所述处理器,在判断所述可穿戴设备从所述佩戴者身上脱落时,还用于根据所述第二传感器采集的所述可穿戴设备的佩戴者的活动信息,判断所述佩戴者所处的情景模式;射频电路,用于在所述处理器的控制下,根据所述佩戴者所处的情景模式发送与所述情景模式对应的提示。
- 根据权利要求15所述的可穿戴设备,所述第一传感器为体温传感器,所述第二传感器包括三轴加速度计传感器和陀螺仪传感器,所述第二传感器还包括GPS传感器和蓝牙传感器中的一个;所述体温传感器用于采集所述佩戴者的生理参数信息的体温信号信息;所述处理器,在判断所述可穿戴设备从所述佩戴者身上脱落时,还用于根据所述第二传感器采集的所述可穿戴设备的佩戴者的活动信息,判断所述佩戴者所处的情景模式,具体为:所述处理器,在判断所述可穿戴设备从所述佩戴者身上脱落时,还用于根据所述三轴加速度计传感器和所述陀螺仪传感器采集的所述佩戴者的活动信息的活动状态信息,判断所述佩戴者的活动状态信息是否存在异常;所述处理器还用于根据所述GPS传感器或所述蓝牙传感器采集的所述佩戴者的活动信息的活动区域信息,判断所述佩戴者是否处于预设的活动区域;所述处理器,还用于根据所述佩戴者的活动状态信息和活动区域信息,判断所述佩戴者所处的情景模式。
- 根据权利要求15或16所述的可穿戴设备,其特征在于,所述情景模式包括:危险状态低的情景模式、危险状态高的情景模式、可穿戴设备正常摘掉的情景模式和可穿戴设备意外脱落的情景模式中的一种或多种。
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