CN116898425A - Fall detection method and device, electronic equipment and storage medium - Google Patents
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- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
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- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
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Abstract
The invention provides a fall detection method, a fall detection device, electronic equipment and a storage medium, wherein the fall detection method comprises the following steps: acquiring human body motion data measured by at least two motion sensors worn by a user and acquiring human body physiological data measured by physiological sensors worn by the user; judging whether the user falls according to the human body movement data measured by the plurality of movement sensors and the movement data threshold range which is correspondingly set, and obtaining a first judgment result, wherein when the human body movement data exceeds the movement data threshold range, the first judgment result judges that the user falls; judging whether the user falls according to the human physiological data and a preset physiological data threshold range to obtain a second judgment result, wherein the second judgment result is that the user falls when the human physiological data exceeds the physiological data threshold range; and when the first judging result and the second judging result are both that the user falls, generating alarm information.
Description
Technical Field
The invention relates to the technical field of intelligent medical treatment, in particular to a fall detection method, a fall detection device, electronic equipment and a storage medium.
Background
With the increasing population ageing, the most common problem for elderly people in daily life is falling. Falls have become a ubiquitous risk in the elderly population, bringing great trouble and accidental injury to their lives. Therefore, prevention, detection and timely alarm of falls, and safeguards against falls have become important issues of concern in recent years.
Existing fall detection devices typically employ a single motion sensor, and fall detection is performed based on motion signals acquired by the single motion sensor. However, because the movement of the human body is complex, existing fall detection by a single sensor is prone to missed detection or detection errors.
Disclosure of Invention
The invention provides a fall detection method, a fall detection device, electronic equipment and a storage medium, which are used for solving the defect that fall detection is easy to miss detection or is wrong in detection by a single sensor in the prior art and realizing the function of accurately detecting fall behaviors.
In a first aspect, the invention provides a fall detection method comprising: acquiring human body motion data measured by at least two motion sensors worn by a user and acquiring human body physiological data measured by physiological sensors worn by the user; judging whether the user falls according to human body motion data measured by a plurality of motion sensors and a corresponding set motion data threshold range to obtain a first judgment result, wherein when the human body motion data exceeds the motion data threshold range, the first judgment result judges that the user falls; judging whether the user falls according to the human physiological data and a preset physiological data threshold range to obtain a second judgment result, wherein the second judgment result is that the user falls when the human physiological data exceeds the physiological data threshold range; and when the first judging result and the second judging result are both that the user falls, generating alarm information.
According to the fall detection method provided by the invention, the motion sensor comprises a first motion sensor worn at the trunk of the user and a second motion sensor worn at the limbs of the user, and the acquiring of human motion data measured by at least two motion sensors worn by the user comprises: and acquiring first human body motion data measured by the first motion sensor and acquiring second human body motion data measured by the second motion sensor.
According to the method for detecting falling provided by the invention, whether the user falls or not is judged according to the human body motion data measured by a plurality of motion sensors and the corresponding set motion data threshold range, so as to obtain a first judgment result, and the method comprises the following steps: judging whether the user falls down according to the first human body movement data and a preset first movement data threshold range, and obtaining a third judgment result; judging whether the user falls according to the second human body movement data and a preset second human body movement data threshold range, and obtaining a fourth judgment result; and obtaining the second judgment result according to the third judgment result and the fourth judgment result.
According to the method for detecting falling provided by the invention, whether the user falls or not is judged according to the human body motion data measured by a plurality of motion sensors and the corresponding set motion data threshold range, and the first judgment result comprises: continuously comparing human body motion data obtained by measuring a plurality of motion sensors in real time with the motion data threshold range to obtain the first judgment result; and when the human body movement data continuously exceeds the movement data threshold range within a preset time range, the first judgment result judges that the user falls down.
According to the method for detecting the falling, the determining whether the falling action of the user occurs according to the physiological data of the human body and the preset physiological data threshold range, to obtain a second determination result, comprises the following steps: continuously comparing the human physiological data measured by the physiological sensor in real time with the physiological data threshold range to obtain the second judgment result; and when the physiological data of the human body continuously exceeds the physiological data threshold range in a preset time range, or the frequency of the physiological data of the human body exceeding the physiological data threshold range in the preset time range is larger than the preset frequency, the second judgment result judges that the user falls.
According to the fall detection method provided by the invention, the human physiological data comprises at least one of the following: heart rate data, blood pressure data, body temperature data.
According to the fall detection method provided by the invention, the fall detection method further comprises the following steps: acquiring the moving distance of the user in preset time according to the displacement sensor worn by the user; and when the moving distance is smaller than the preset safe displacement distance, an alarm signal is sent out.
In a second aspect, the invention also provides a fall detection apparatus comprising: the system comprises a data acquisition module, a first judgment module, a second judgment module and a fall alarm module, wherein the data acquisition module is used for acquiring human body motion data measured by at least two motion sensors worn by a user and acquiring human body physiological data measured by physiological sensors worn by the user; the first judging module is used for judging whether the user falls according to the human body movement data measured by the plurality of movement sensors and the movement data threshold range which is correspondingly set to obtain a first judging result, wherein when the human body movement data exceeds the movement data threshold range, the first judging result judges that the user falls; the second judging module is used for judging whether the user falls according to the human physiological data and a preset physiological data threshold range to obtain a second judging result, wherein the second judging result is that the user falls when the human physiological data exceeds the physiological data threshold range; and the falling alarm module is used for generating alarm information when the first judgment result and the second judgment result are that the user falls.
In a third aspect, the invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of any one of the fall detection methods described above when the program is executed.
In a fourth aspect, the invention also provides a non-transitory computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of a fall detection method as described in any of the above.
According to the fall detection method, the fall detection device, the electronic equipment and the storage medium, the fall behavior is judged by the human body motion data measured by the plurality of motion sensors on the user, and meanwhile, the fall behavior is further judged by the human body physiological data measured by the physiological sensors, so that whether the user falls or not can be accurately identified, alarm information is generated, the possibility of casualties caused by falling is reduced, and the life safety of the user is ensured.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a fall detection method provided by the invention;
fig. 2 is a schematic structural diagram of a fall detection device provided by the present invention;
fig. 3 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The fall detection method, apparatus, electronic device and storage medium of the present invention are described below with reference to fig. 1 to 3.
Fig. 1 is a schematic flow chart of a fall detection method according to the present invention, as shown in fig. 1, the method includes the following steps:
s101, acquiring human body motion data measured by at least two motion sensors worn by a user and acquiring human body physiological data measured by physiological sensors worn by the user;
s102, judging whether the user falls according to human body motion data measured by a plurality of motion sensors and a corresponding set motion data threshold range to obtain a first judgment result, wherein when the human body motion data exceeds the motion data threshold range, the first judgment result judges that the user falls;
s103, judging whether the user falls according to the human physiological data and a preset physiological data threshold range to obtain a second judgment result, wherein the second judgment result is that the user falls when the human physiological data exceeds the physiological data threshold range;
s104, when the first judging result and the second judging result are that the user falls, alarm information is generated.
According to the fall detection method, the fall detection device, the electronic equipment and the storage medium, the fall behavior is judged by the human body motion data measured by the plurality of motion sensors on the user, and meanwhile, the fall behavior is further judged by the human body physiological data measured by the physiological sensors, so that whether the user falls or not can be accurately identified, alarm information is generated, the possibility of casualties caused by falling is reduced, and the life safety of the user is ensured.
Possible implementations of the above two steps in the specific embodiments are further described below.
S101, acquiring human body motion data measured by at least two motion sensors worn by a user and acquiring human body physiological data measured by physiological sensors worn by the user.
The motion sensor mentioned in the present invention may be an acceleration sensor or a gyro sensor, the human motion data may be acceleration data or angular velocity data, the physiological sensor may be a heart rate sensor, a blood pressure sensor, a respiration sensor, etc., and the human physiological data may be heart rate data, blood pressure data, body temperature data, etc.
It can be understood that the monitoring device comprising the motion sensor and the physiological sensor is worn on the user, and the device on the user at least comprises two or more motion sensors, so that the data on the sensors can be acquired in real time; specifically, the acceleration change of different parts of the human body can be measured through two acceleration sensors, or the angular velocity or angular change of different parts of the human body can be measured through two gyroscope sensors; meanwhile, one or more physiological sensors can be arranged to measure heart rate variation or blood pressure variation of a human body, so that abnormal variation of heart rate can be conveniently detected after falling, acceleration or slowing of heart rate can occur, or abnormal variation of blood pressure can be detected by the blood pressure sensors, and rising or lowering of blood pressure can occur.
S102, judging whether the user falls according to human body motion data measured by a plurality of motion sensors and a corresponding set motion data threshold range, and obtaining a first judgment result, wherein when the human body motion data exceeds the motion data threshold range, the first judgment result judges that the user falls.
It will be appreciated that depending on the nature of the fall behaviour, a corresponding range of motion data thresholds may be set. For example, the old person generally moves at a slower rate, a threshold range of movement data may be set based on previous data of the old person, and when the acceleration exceeds the threshold range or the angular velocity changes beyond the fixed threshold range, it may be determined that the old person is falling.
In order to detect whether the user falls, a plurality of sensors can be arranged on the user, whether the user falls or not is judged through human body motion data measured by the plurality of motion sensors and a corresponding set motion data threshold range, and when the human body motion data exceeds the motion data threshold range, a first judgment result judges that the user falls. When the human body movement data is within the movement data threshold range, the first judgment result judges that the user does not fall.
And S103, judging whether the user falls according to the human physiological data and a preset physiological data threshold range to obtain a second judgment result, wherein the second judgment result is that the user falls when the human physiological data exceeds the physiological data threshold range.
It can be appreciated that when a user falls, there is a certain change in physiological data of the human body, for example, after the fall, the heart rate of the human body may be increased or the blood pressure may be increased; therefore, in order to detect whether the user has a falling action, the physiological sensor can be used for collecting the physiological data of the user in real time, a corresponding physiological data threshold range is set according to the characteristics of the falling action, the collected physiological data of the human body is compared with the preset physiological data threshold range, and when the physiological data of the human body is higher than or lower than the physiological data threshold range, the second judgment result is judged that the falling action of the user occurs. When the human physiological data is within the physiological data threshold range, the second determination result determines that the user does not fall.
S104, when the first judging result and the second judging result are that the user falls, alarm information is generated.
It can be understood that after the first judgment result and the second judgment result are obtained, the fall alarm information is generated only when the first judgment result and the second judgment result are both judged to be the fall behaviors of the user.
In this embodiment, the monitoring device worn on the user body may be in communication connection with the user monitoring center, the user manager, or the terminal of the user relative, and when it is determined that the user falls, the alarm information may be sent to the user monitoring center, the user manager, or the terminal of the user relative.
It is also conceivable that, when comparing the collected physiological data of the human body with a preset physiological data threshold range, if the physiological data of the human body is continuously higher or lower than the physiological data threshold range within a preset safety time, a prompt message is sent to a user monitoring center, a user manager, or a terminal of a relative of the user.
According to the fall detection method provided by the invention, the fall behaviors are judged by the human body motion data measured by the plurality of motion sensors on the user, and meanwhile, the fall behaviors are further judged by the human body physiological data measured by the physiological sensors, so that whether the user falls can be more accurately identified, alarm information is generated, the possibility of casualties caused by falling is reduced, and the life safety of the user is ensured.
Optionally, the motion sensor includes a first motion sensor worn at the torso of the user and a second motion sensor worn at the extremities of the user, and the acquiring human motion data measured by the at least two motion sensors worn by the user includes:
and acquiring first human body motion data measured by the first motion sensor and acquiring second human body motion data measured by the second motion sensor.
It will be appreciated that first person movement data for a torso region of a user may be obtained by a first movement sensor worn at the torso of the user. Second human motion data of the user's limb portion may be acquired by a second motion sensor worn at the user's limb.
Optionally, the determining whether the user falls according to the human motion data measured by the motion sensors and the motion data threshold range set correspondingly to obtain a first determination result includes:
judging whether the user falls down according to the first human body movement data and a preset first movement data threshold range, and obtaining a third judgment result;
judging whether the user falls according to the second human body movement data and a preset second human body movement data threshold range, and obtaining a fourth judgment result;
and obtaining the second judgment result according to the third judgment result and the fourth judgment result.
It will be appreciated that the movement data of different parts of the human body will be different and different movement data of the human body can be obtained through different parts of the body. For example, the acceleration data and the angular velocity data of the trunk area are generally larger than those of the trunk area. Thus, different human motion data threshold ranges may be set according to different body parts.
In this embodiment, first human body motion data may be obtained through a first motion sensor worn on the trunk of the user, a corresponding first motion data threshold range is set according to the trunk of the human body, whether the first human body motion data is within the preset first motion data threshold range is determined, and if the first human body motion data exceeds the preset first motion data threshold range, the third determination result determines that the user falls down; and if the first human body movement data is within the preset first movement data threshold range, the third judgment result is that the user does not fall.
The method comprises the steps that second human body movement data can be obtained through a second movement sensor worn on the limbs of a user, a corresponding second movement data threshold range is set according to the limbs of the user, whether the second human body movement data is within the preset second movement data threshold range is determined, and if the second human body movement data exceeds the preset second movement data threshold range, a fourth judgment result is judged that the user falls down; and if the second human body movement data is within the preset second movement data threshold range, the fourth judgment result is that the user does not fall.
And when the third judging result and the fourth judging result are both judged that the user falls, the second judging result is judged that the user falls.
Optionally, the determining whether the user falls according to the human motion data measured by the motion sensors and the motion data threshold range set correspondingly, to a first determination result, includes:
continuously comparing human body motion data obtained by measuring a plurality of motion sensors in real time with the motion data threshold range to obtain the first judgment result;
and when the human body movement data continuously exceeds the movement data threshold range within a preset time range, the first judgment result judges that the user falls down.
It can be understood that the data acquired by the motion sensor are measured in real time, and the user is determined to fall when the human motion data continuously exceeds the motion data threshold range within a preset time by continuously comparing the acquired human motion data with the motion data threshold range.
Specifically, taking an acceleration sensor as an example, the acquired acceleration data is compared with a set motion data threshold range. And if the acceleration data of the user is continuously larger than the threshold range of the motion data in the preset time, judging that the user falls.
Optionally, the determining whether the user falls according to the physiological data of the human body and the preset physiological data threshold range to obtain a second determination result includes:
continuously comparing the human physiological data measured by the physiological sensor in real time with the physiological data threshold range to obtain the second judgment result;
and when the physiological data of the human body continuously exceeds the physiological data threshold range in a preset time range, or the frequency of the physiological data of the human body exceeding the physiological data threshold range in the preset time range is larger than the preset frequency, the second judgment result judges that the user falls.
It can be understood that the data obtained by the physiological sensor is obtained by real-time measurement, and the obtained physiological data of the human body is continuously compared with the physiological data threshold range, and when the physiological data of the human body continuously exceeds the motion data threshold range in a preset time or the frequency of the physiological data of the human body exceeding the physiological data threshold range in the preset time range is greater than the preset frequency, the falling action of the user is judged.
Specifically, taking the heart rate sensor as an example, when the obtained heart rate data is higher or lower than the threshold range of the physiological data, the user is indicated that the body is in an abnormal state at the moment, and meanwhile, the heart rate data is at a critical position exceeding the threshold range, which is also in an abnormal state, so that the user is also determined to fall when the heart rate data exceeds the threshold range for a certain number of times within a certain time.
Optionally, the method further comprises: acquiring the moving distance of the user in preset time according to the displacement sensor worn by the user;
and when the moving distance is smaller than the preset safe displacement distance, an alarm signal is sent out.
It can be understood that the monitoring device worn by the user further comprises a displacement sensor, and after the user is judged to fall and alarm information is generated, the displacement condition of the user is continuously monitored, and the moving distance of the user in the preset time is obtained. When the user does not have enough displacement within the preset time, an alarm signal is sent out, and the monitoring equipment is controlled to send out alarm sounds such as beeping sounds.
Because the user can think that the user falls down more seriously when not enough displacement in the preset time, the life and health of the user can not be guaranteed under the condition of sending alarm information, and therefore the alarm signal can be sent out, the user can get four sides of attention, and the life and health of the user can be further guaranteed.
The fall detection device provided by the invention will be described below, and the fall detection device described below and the fall detection method described above can be referred to correspondingly to each other.
The fall detection device provided by the embodiment of the invention, as shown in fig. 2, mainly comprises a data acquisition module 201, a first judgment module 202, a second judgment module 203 and a fall alarm module 204, wherein the data acquisition module 201 is used for acquiring human motion data measured by at least two motion sensors worn by a user and acquiring human physiological data measured by physiological sensors worn by the user; the first judging module 202 is configured to judge whether the user falls according to the human body motion data measured by the plurality of motion sensors and the motion data threshold ranges set correspondingly, so as to obtain a first judging result, where the first judging result determines that the user falls when the human body motion data exceeds the motion data threshold ranges; the second judging module 203 is configured to judge whether the user falls according to the physiological data of the human body and a preset physiological data threshold range, so as to obtain a second judging result, where the second judging result is that the user falls when the physiological data of the human body exceeds the physiological data threshold range; the fall alarm module 204 is configured to generate alarm information when the first determination result and the second determination result are both that the user has a fall behavior.
According to the fall detection device provided by the invention, the fall behavior is judged by the human body motion data measured by the plurality of motion sensors on the user, and meanwhile, the fall behavior is further judged by the human body physiological data measured by the physiological sensors, so that whether the user falls or not can be accurately identified, alarm information is generated, the possibility of casualties caused by falling is reduced, and the life safety of the user is ensured.
Fig. 3 illustrates a physical schematic diagram of an electronic device, as shown in fig. 3, where the electronic device may include: processor 301, communication interface (Communications Interface) 302, memory (memory) 303 and communication bus 304, wherein processor 301, communication interface 302, memory 303 accomplish the communication between each other through communication bus 304. The processor 301 may invoke logic instructions in the memory 303 to perform the fall detection method provided by the method embodiments described above, including, for example: acquiring human body motion data measured by at least two motion sensors worn by a user and acquiring human body physiological data measured by physiological sensors worn by the user; judging whether the user falls according to human body motion data measured by a plurality of motion sensors and a corresponding set motion data threshold range to obtain a first judgment result, wherein when the human body motion data exceeds the motion data threshold range, the first judgment result judges that the user falls; judging whether the user falls according to the human physiological data and a preset physiological data threshold range to obtain a second judgment result, wherein the second judgment result is that the user falls when the human physiological data exceeds the physiological data threshold range; and when the first judging result and the second judging result are both that the user falls, generating alarm information.
Further, the logic instructions in the memory 303 may be implemented in the form of software functional units and stored in a computer readable storage medium when sold or used as a stand alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, randomAccess Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In another aspect, the invention also provides a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, enable the computer to perform the fall detection method provided by the method embodiments described above, the method comprising, for example: acquiring human body motion data measured by at least two motion sensors worn by a user and acquiring human body physiological data measured by physiological sensors worn by the user; judging whether the user falls according to human body motion data measured by a plurality of motion sensors and a corresponding set motion data threshold range to obtain a first judgment result, wherein when the human body motion data exceeds the motion data threshold range, the first judgment result judges that the user falls; judging whether the user falls according to the human physiological data and a preset physiological data threshold range to obtain a second judgment result, wherein the second judgment result is that the user falls when the human physiological data exceeds the physiological data threshold range; and when the first judging result and the second judging result are both that the user falls, generating alarm information.
In yet another aspect, the invention also provides a non-transitory computer-readable storage medium having stored thereon a computer program which, when executed by a processor, is implemented to perform the fall detection method provided by the above-described method embodiments, the method for example comprising: acquiring human body motion data measured by at least two motion sensors worn by a user and acquiring human body physiological data measured by physiological sensors worn by the user; judging whether the user falls according to human body motion data measured by a plurality of motion sensors and a corresponding set motion data threshold range to obtain a first judgment result, wherein when the human body motion data exceeds the motion data threshold range, the first judgment result judges that the user falls; judging whether the user falls according to the human physiological data and a preset physiological data threshold range to obtain a second judgment result, wherein the second judgment result is that the user falls when the human physiological data exceeds the physiological data threshold range; and when the first judging result and the second judging result are both that the user falls, generating alarm information.
According to the electronic equipment, the non-transitory computer readable storage medium and the computer program product provided by the embodiment of the invention, through executing the steps of the fall detection method described in the embodiments, the fall behaviors are judged by the human body motion data measured by the plurality of motion sensors on the body of the user, and meanwhile, the fall behaviors are further judged by the human body physiological data measured by the physiological sensors, so that whether the fall behaviors exist or not can be more accurately identified, alarm information is generated, the possibility of casualties caused by falling is reduced, and the life safety of the user is ensured.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A fall detection method, comprising:
acquiring human body motion data measured by at least two motion sensors worn by a user and acquiring human body physiological data measured by physiological sensors worn by the user;
judging whether the user falls according to human body motion data measured by a plurality of motion sensors and a corresponding set motion data threshold range to obtain a first judgment result, wherein when the human body motion data exceeds the motion data threshold range, the first judgment result judges that the user falls;
judging whether the user falls according to the human physiological data and a preset physiological data threshold range to obtain a second judgment result, wherein the second judgment result is that the user falls when the human physiological data exceeds the physiological data threshold range;
and when the first judging result and the second judging result are both that the user falls, generating alarm information.
2. A fall detection method as claimed in claim 1, wherein the motion sensor comprises a first motion sensor worn at the torso of the user and a second motion sensor worn at the limbs of the user, the acquiring human motion data measured by at least two motion sensors worn by the user comprising:
and acquiring first human body motion data measured by the first motion sensor and acquiring second human body motion data measured by the second motion sensor.
3. A fall detection method according to claim 2, wherein the determining whether the user falls according to the human body motion data measured by the plurality of motion sensors and the corresponding set motion data threshold range, to obtain a first determination result, comprises:
judging whether the user falls down according to the first human body movement data and a preset first movement data threshold range, and obtaining a third judgment result;
judging whether the user falls according to the second human body movement data and a preset second human body movement data threshold range, and obtaining a fourth judgment result;
and obtaining the second judgment result according to the third judgment result and the fourth judgment result.
4. A fall detection method according to claim 1, wherein the determining whether the user falls according to the human body motion data measured by the plurality of motion sensors and the corresponding set motion data threshold range, to a first determination result, comprises:
continuously comparing human body motion data obtained by measuring a plurality of motion sensors in real time with the motion data threshold range to obtain the first judgment result;
and when the human body movement data continuously exceeds the movement data threshold range within a preset time range, the first judgment result judges that the user falls down.
5. The fall detection method according to claim 1, wherein the determining whether the user falls according to the physiological data of the human body and a preset physiological data threshold range, to obtain a second determination result, includes:
continuously comparing the human physiological data measured by the physiological sensor in real time with the physiological data threshold range to obtain the second judgment result;
and when the physiological data of the human body continuously exceeds the physiological data threshold range in a preset time range, or the frequency of the physiological data of the human body exceeding the physiological data threshold range in the preset time range is larger than the preset frequency, the second judgment result judges that the user falls.
6. A fall detection method as claimed in claim 1, wherein the human physiological data comprises at least one of: heart rate data, blood pressure data, body temperature data.
7. A fall detection method as claimed in claim 1, further comprising:
acquiring the moving distance of the user in preset time according to the displacement sensor worn by the user;
and when the moving distance is smaller than the preset safe displacement distance, an alarm signal is sent out.
8. A fall detection device, comprising:
the data acquisition module is used for acquiring human body motion data measured by at least two motion sensors worn by a user and acquiring human body physiological data measured by physiological sensors worn by the user;
the first judging module is used for judging whether the user falls according to the human body movement data measured by the plurality of movement sensors and the movement data threshold range which is correspondingly set to obtain a first judging result, wherein when the human body movement data exceeds the movement data threshold range, the first judging result judges that the user falls;
the second judging module is used for judging whether the user falls according to the human physiological data and a preset physiological data threshold range to obtain a second judging result, wherein the second judging result is that the user falls when the human physiological data exceeds the physiological data threshold range;
and the falling alarm module is used for generating alarm information when the first judgment result and the second judgment result are that the user falls.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor performs the steps of the fall detection method as claimed in any one of claims 1 to 7 when the program is executed.
10. A non-transitory computer readable storage medium having stored thereon a computer program, which when executed by a processor performs the steps of a fall detection method as claimed in any of claims 1 to 7.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103961108A (en) * | 2013-02-06 | 2014-08-06 | 由田新技股份有限公司 | Tumbling detecting method |
| CN106384481A (en) * | 2016-11-01 | 2017-02-08 | 西安培华学院 | Remote Internet-based first-aid alarm device with fall posture judgment function |
| US20170109990A1 (en) * | 2015-10-20 | 2017-04-20 | Micron Electronics LLC | Method and system for fall detection |
| CN116250828A (en) * | 2021-12-09 | 2023-06-13 | 深圳迈瑞生物医疗电子股份有限公司 | Fall detection method and fall detection system |
-
2023
- 2023-08-22 CN CN202311061805.2A patent/CN116898425A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103961108A (en) * | 2013-02-06 | 2014-08-06 | 由田新技股份有限公司 | Tumbling detecting method |
| US20170109990A1 (en) * | 2015-10-20 | 2017-04-20 | Micron Electronics LLC | Method and system for fall detection |
| CN106384481A (en) * | 2016-11-01 | 2017-02-08 | 西安培华学院 | Remote Internet-based first-aid alarm device with fall posture judgment function |
| CN116250828A (en) * | 2021-12-09 | 2023-06-13 | 深圳迈瑞生物医疗电子股份有限公司 | Fall detection method and fall detection system |
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