CN111938588A - Method for detecting sleep state, sleep monitor and storage medium - Google Patents
Method for detecting sleep state, sleep monitor and storage medium Download PDFInfo
- Publication number
- CN111938588A CN111938588A CN202010723356.3A CN202010723356A CN111938588A CN 111938588 A CN111938588 A CN 111938588A CN 202010723356 A CN202010723356 A CN 202010723356A CN 111938588 A CN111938588 A CN 111938588A
- Authority
- CN
- China
- Prior art keywords
- signal
- preset
- motion
- determining
- heart rate
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4806—Sleep evaluation
- A61B5/4809—Sleep detection, i.e. determining whether a subject is asleep or not
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4806—Sleep evaluation
Abstract
The embodiment of the invention relates to the technical field of sleep monitoring, and discloses a method for detecting a sleep state and a sleep monitor. That is, the jogging signals are screened according to the signal energy in periodicity and unit time, the jogging signals with high reliability are screened, and the interference of other signals can be effectively eliminated, so that the judgment accuracy is improved.
Description
Technical Field
The embodiment of the invention relates to the technical field of sleep monitoring, in particular to a method for detecting a sleep state, a sleep monitor and a storage medium.
Background
The sleep state of the human body can intuitively reflect the deep sleep and light sleep proportion in the sleep cycle of the human body, and can monitor the sleep habit and the health state of the user for a long time. In order to monitor the sleep state, the related sleep health care products monitor signals of breathing, heart rate and the like of a human body in the sleep state, and the sleep condition of the user all night is analyzed and evaluated according to the physical sign signals.
However, in some sleep monitoring products on the market at present, signals acquired by sensors are directly analyzed and identified, an internal identification algorithm is simple, accuracy is not high, and an output sleep report is greatly different from an actual sleep condition.
Disclosure of Invention
The embodiment of the invention mainly solves the technical problem of providing a method for detecting and measuring the sleep state, a sleep monitor and a storage medium, which can accurately detect the sleep state of a user.
In order to solve the above technical problem, in a first aspect, an embodiment of the present invention provides a method for detecting a sleep state, including:
acquiring a micro-motion signal of a target object, wherein the target object is an object relative to a bed;
judging whether the inching signal is a periodic signal or not;
if yes, judging whether the signal energy of the micro-motion signal in unit time falls into a preset energy threshold interval;
if yes, determining the physical sign parameters of the target object according to the micro-motion signal;
and determining the sleep state of the target object according to the sign parameters.
In some embodiments, the determining whether the inching signal is a periodic signal includes:
acquiring the inching signal with a first preset time length;
performing autocorrelation processing on the inching signal within the first preset time length to obtain an autocorrelation signal of the inching signal;
determining the maximum value of the peak value of the autocorrelation signal within the first preset time length;
and if the maximum value of the peak value is greater than or equal to a preset threshold value, determining that the inching signal is a periodic signal.
In some embodiments, said determining a vital sign parameter of said target subject from said micro-motion signal comprises:
filtering the micro-motion signal to remove an interference signal in the micro-motion signal;
performing band-pass filtering on the micro-motion signal after filtering processing by using a first preset frequency band to obtain a first micro-motion signal;
performing band-pass filtering on the micro-motion signal after filtering processing by using a second preset frequency band to obtain a second micro-motion signal, wherein the wave band frequency of the second preset frequency band is greater than the wave band frequency of the second preset frequency band, and the wave band frequency of the second preset frequency band is not overlapped with the wave band frequency of the first preset frequency band;
acquiring the signal quality of the first inching signal, and determining the first inching signal with the signal quality meeting a preset quality condition as a respiratory signal;
acquiring the signal quality of the second micro-motion signal, and determining that the second micro-motion signal with the signal quality meeting the preset quality condition is a heart rate and body motion mixed signal;
and determining the sign parameters of the target object according to the respiration signal and the heart rate and body movement mixed signal.
In some embodiments, the filtering process comprises a power frequency notching process.
In some embodiments, the signal quality is a standard deviation of a signal peak value, and the preset quality condition is that the standard deviation is smaller than a preset standard deviation threshold.
In some embodiments, the vital sign parameters include a state relative to a bed, a physical movement condition, a heart rate, and a respiration rate;
the determining of the sign parameters of the target subject according to the respiration signal and the heart rate and body movement mixed signal comprises:
according to the heart rate and body movement mixed signal, acquiring the periodicity of the heart rate and body movement mixed signal within a second preset time length and the signal energy of the heart rate and body movement mixed signal within the second preset time length in unit time;
if the heart rate and body motion mixed signal in the second preset time length is determined to be an aperiodic signal according to the periodicity, and the signal energy of the heart rate and body motion mixed signal in unit time in the second preset time length is lower than the lower limit of the preset energy threshold interval, determining that the target object is in a bed leaving state in the second preset time length, otherwise, determining that the target object is in a bed in state in the second preset time length;
when the target object is in a bed state within the second preset time length, if the signal energy of the heart rate and body motion mixed signal within the second preset time length in unit time is greater than or equal to a first preset energy threshold value, determining that the target object generates body motion within the second preset time length, otherwise, determining that the target object does not generate body motion within the second preset time length;
when the target object does not generate body motion within the second preset time, determining the heart rate of the target object within the second preset time according to the heart rate and body motion mixed signal within the second preset time, and determining the breathing rate of the target object within the second preset time according to the breathing signal within the second preset time.
In some embodiments, the physical sign parameters further include a body movement type and a body movement duration, wherein the body movement type is one of a large body movement and a small body movement;
the method for determining the physical sign parameters of the target object according to the respiration signal and the heart rate and body movement mixed signal further comprises the following steps:
when the target object generates body motion within the second preset duration, determining a time interval between a body motion starting point and a body motion stopping point as body motion duration, wherein the body motion starting point is a time point when the signal energy in the heart rate and body motion mixed signal unit time is increased from being smaller than the first preset energy threshold value to the first preset energy threshold value, and the body motion stopping point is a time point when the signal energy in the heart rate and body motion mixed signal unit time is decreased from being larger than the first preset energy threshold value to the first preset energy threshold value;
if the maximum value of the signal energy of the heart rate and body motion mixed signal in the unit time between the body motion starting point and the body motion stopping point is larger than or equal to a second preset energy threshold value, determining that the body motion type of the target object in the second preset time length is general motion;
and if the maximum value of the signal energy of the heart rate and body motion mixed signal in the unit time between the body motion starting point and the body motion stopping point is smaller than the second preset energy threshold value and larger than or equal to a third preset energy threshold value, determining that the body motion type of the target object in the second preset time period is small body motion.
In some embodiments, the sleep state is one of wakefulness, light sleep and deep sleep, and the determining the sleep state of the target subject according to the physical parameters includes:
if the number of times of the body movement within a third preset time period is smaller than a first preset threshold, the standard deviation of the heart rate within the third preset time period is smaller than a first heart rate threshold, and the standard deviation of the respiration rate within the third preset time period is smaller than a first respiration rate threshold, determining that the sleep state is deep sleep, wherein the third preset time period is longer than a second preset time period;
if the number of times of the gross movement within a third preset time length is greater than the first preset threshold and less than a second preset threshold, determining that the sleep state is light sleep;
and if the number of times of the gross movement within a third preset time length is greater than the second preset threshold value, determining that the sleep state is aroused.
In order to solve the above technical problem, in a second aspect, an embodiment of the present invention provides a sleep monitor, including:
the piezoelectric sensor is used for acquiring a micromotion electric signal;
the control processing module, the control processing module with piezoelectric sensor is connected, the control processing module is used for to the fine motion signal of telecommunication handles to acquire the fine motion signal, the control processing module includes:
at least one processor, and
a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of the first aspect as described above.
In order to solve the above technical problem, in a third aspect, the present invention provides a non-volatile computer-readable storage medium storing computer-executable instructions that, when executed by a sleep monitor, cause the sleep monitor to perform the method of the second aspect.
The embodiment of the invention has the following beneficial effects: different from the situation in the prior art, in the method for detecting a sleep state provided in the embodiment of the present invention, whether a micro-motion signal of a target object is a periodic signal is determined by obtaining the micro-motion signal, when the micro-motion signal is the periodic signal, whether signal energy of the micro-motion signal in unit time falls into a preset energy threshold interval is further determined, if yes, a physical sign parameter of the target object is determined according to the micro-motion signal, and the sleep state of the target object can be accurately determined according to the physical sign parameter. That is, the jogging signals are screened according to the signal energy in periodicity and unit time, the jogging signals with high reliability are screened, and the interference of other signals can be effectively eliminated, so that the judgment accuracy is improved.
Drawings
One or more embodiments are illustrated by way of example in the accompanying drawings, which correspond to the figures in which like reference numerals refer to similar elements and which are not to scale unless otherwise specified.
Fig. 1 is a schematic diagram of an application system of a method for detecting a sleep state according to an embodiment of the present invention;
FIG. 2 is a schematic circuit diagram of the sleep monitoring apparatus shown in FIG. 1;
fig. 3 is a flowchart illustrating a method for detecting a sleep state according to an embodiment of the present invention;
FIG. 4 is a sub-flowchart of step 220 in FIG. 3;
FIG. 5 is a schematic view of a sub-flow chart of step 240 in FIG. 3;
FIG. 6 is a schematic view of a sub-process flow of step 246 of FIG. 5;
FIG. 7 is another sub-flow diagram of step 246 of FIG. 5;
FIG. 8 is a sub-flowchart of step 250 in FIG. 3;
fig. 9 is a schematic structural diagram of a sleep monitor according to another embodiment of the present invention.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the invention, but are not intended to limit the invention in any way. It should be noted that variations and modifications can be made by persons skilled in the art without departing from the spirit of the invention. All falling within the scope of the present invention.
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
It should be noted that, if not conflicted, the various features of the embodiments of the invention may be combined with each other within the scope of protection of the present application. Additionally, while functional block divisions are performed in apparatus schematics, with logical sequences shown in flowcharts, in some cases, steps shown or described may be performed in sequences other than block divisions in apparatus or flowcharts. Further, the terms "first," "second," "third," and the like, as used herein, do not limit the data and the execution order, but merely distinguish the same items or similar items having substantially the same functions and actions.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
Referring to fig. 1, a schematic diagram of an application system of an embodiment of a method for detecting a sleep state according to the present invention is shown, where the system 100 includes: the sleep monitoring system comprises a sleep monitoring device 10, a server 20 and a mobile terminal 30, wherein the sleep monitoring device 10 and the server 20 can be in communication connection in a wired or wireless mode, and the mobile terminal 30 and the server 20 can be in communication connection in a wired or wireless mode.
The sleep monitoring device 10 sends the monitored sleep state of the user to the server 20, generates a sleep state report or a sleep state report after statistical processing by the server 20, and sends the sleep state report or the sleep state report to the mobile terminal 30. Accordingly, the user can clearly understand the sleep state and the change of the sleep state from the mobile terminal 30.
The sleep monitoring device 10 comprises a sensor 11, a control device 12 and a power adapter 13, wherein the sensor 11 is connected with the control device 12, for example, a connecting wire is connected, and the control device 12 is detachably connected with the power adapter 13 so as to adapt to different socket interfaces. The sensor 11 is configured to collect a micro-motion electrical signal of the user and send the micro-motion electrical signal to the control device 12, and the control device 12 analyzes and processes the micro-motion electrical signal by using a preset algorithm, so as to obtain a sleep state of the user. The power adapter 13 is used to supply power to the control device 12.
The sensor 11 is a strip-shaped piezoelectric film sensor. The sensor 11 may be placed on or under a mattress and directly under the user's armpit. After the user lies in the bed, because breathing, heartbeat and body movement can make the user's health produce the fine motion, lead to sensor 11 produces deformation, gathers the fine motion signal of telecommunication, and will the fine motion signal of telecommunication passes through the transmission line and transmits to controlling means 12 carries out the operation, obtains user's sleep state and sign parameter.
Referring to fig. 1 and fig. 2, the control device 12 includes a housing 121, and a control processing module 122, a power supply module 123 and a communication module 124 which are accommodated in the housing 121. The control processing module 122 is configured to process and analyze the micro-motion electrical signal collected by the sensor 11 to obtain a sleep state, the communication module 124 is configured to be in communication connection with the server 20, and the power supply module 123 is configured to supply power to the control processing module 122 and the communication module 124.
The control processing module 122 includes a charge amplifier 1221, a filter 1222, and a controller 1223, wherein an input terminal of the charge amplifier 1221 is connected to the sensor 11, an output terminal of the charge amplifier 1221 is connected to an input terminal of the filter 1222, and an output terminal of the filter 1222 is connected to the controller 1223. The micro-motion electrical signal collected by the sensor 11 is amplified by the charge amplifier 1221, and filtered by the filter 1222, and after the interference signal is eliminated, the micro-motion electrical signal is sent to the controller 1223. The controller 1223 is configured to provide computing and control capabilities to control the sleep monitoring device 10 to perform corresponding monitoring tasks, for example, to control the sleep monitoring device 10 to perform any of the methods for detecting sleep states provided by the embodiments of the invention described below.
The controller 1223 includes the singlechip, and the singlechip can adopt 51 series, Ardu i no series, STM32 series etc.. In other embodiments, the controller 1223 may also be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), an arm (acorn RISC machine), or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination of these components; but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine; or as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.
The power supply module 123 includes a USB male head 1231, a first linear regulator 1232 and a second linear regulator 1233, the USB male head 1231 extends out of the casing 121, and the first linear regulator 1232 and the second linear regulator 1233 are contained in the casing 121. The USB male connector 1231 is connected to the first linear regulator 1232 and the second linear regulator 1233, respectively, an output end of the first linear regulator 1232 is connected to the control processing module 122, and an output end of the second linear regulator 1233 is connected to the communication module 124. The control processing module 122 and the communication module are respectively supplied with power by two linear voltage regulators 124, so as to prevent the high-frequency signal generated by the communication module 124 from being connected into the power supply module 123 and interfering with the micro-motion electric signal.
The server 20 may be a server, such as a rack server, a blade server, a tower server, or a rack server, or may be a server cluster composed of a plurality of servers, or a cloud computing service center.
The mobile terminal 30 may be a terminal device with a display screen, such as a smart phone, a tablet computer, or a notebook computer, and the smart phone is taken as an example in fig. 1.
The sleep monitoring device 10 analyzes and processes the collected micro-motion electric signal by a preset algorithm to obtain the physical sign parameters and the sleep state, the physical sign parameters comprise heart rate, respiration, body motion conditions, states relative to the bed and the like, and uploads the sleep state and the physical sign parameters to the server 20, and the server 20 counts and generates a sleep report and sends the sleep report to the mobile terminal 30, wherein the sleep report comprises a heart rate curve, a respiration curve, body motion conditions, bed getting-on and getting-off time, a sleep curve and the like. Thus, the user can view the sleep state and the physical sign parameters on the mobile terminal 30, thereby knowing the health state of the user.
The sleep monitoring device 10 may also be communicatively coupled to household appliances in a sleep environment, such as a desk lamp, an air conditioner, an automatic curtain, etc. via bluetooth. Therefore, the sleep monitoring device 10 can be linked with the household appliance to control the sleep environment, for example, an air conditioner can be linked to intelligently regulate and control the temperature and the humidity according to the sleep depth; when a user sleeps and forgets to turn off the desk lamp, the desk lamp can be linked to automatically turn off the lamp according to whether the user sleeps or not, and the user can automatically turn on the desk lamp when waking up at night to drink water or washing the bathroom. When the user gets up in the morning, the curtain can be linked to automatically open when the user is detected to leave the bed.
It should be noted that the structure of the sleep monitoring apparatus 10 is merely an exemplary illustration, and in practical applications, the method for detecting a sleep state provided by the following embodiments of the present invention may be further extended to other suitable sleep products, without being limited to the sleep monitoring apparatus 10 illustrated in fig. 1.
Referring to fig. 3, an embodiment of the invention provides a method for detecting a sleep state, which can be executed by the controller 1223. As shown in fig. 3, the method 200 includes, but is not limited to, the following steps:
step 210: a micro-motion signal of a target object is acquired, the target object being an object relative to a bed.
The inching signal is a signal for determining the sleep state of the target subject and counting the physical parameters of the target subject, and can be a piezoelectric signal. The target object may be an adult or a child. In this embodiment, the micro-motion signal may be obtained by placing a piezoelectric film sensor under the armpit of the target object, and in other embodiments, the piezoelectric film sensor may be placed in a place where it can contact the target object, for example, a sleeping bag or the like. The micro-motion signal reflects all micro-motions of the target object on the bed, such as heartbeat, respiration, body movement, and on or off the bed. It will be appreciated that the micro-motion signal may specifically be acquired at any suitable sampling frequency, for example, continuously in the form of one micro-motion signal every 10 ms.
Step 220: and judging whether the inching signal is a periodic signal, if so, executing step 230.
Since the micro-motion signal reflects all micro-motions of the target object on the bed, and the micro-motions are multiple, such as respiration, heartbeat, and body motion, the micro-motion signal is a mixed signal including a respiration signal, a heart rate signal, a body motion signal, and the like. While some micro-motion is periodic, such as heartbeat and respiration, even if the body motion is not generated on a periodic basis, the body motion occurs less relative to heartbeat and respiration and, therefore, the body motion signal does not affect the period of the micro-motion signal.
However, in a sleep environment, the micro-motion signal may also include other interfering signals. For example, when a fan blows against the bed, the airflow may also act on the sensor to produce a disturbing signal.
In order to ensure the accuracy of the inching signal, before the sleep state is identified, the inching signal is firstly confirmed to be a periodic signal, so that the accuracy of the signal can be ensured, and an interference signal is discharged.
In order to determine the periodicity of the inching signal, in some embodiments, referring to fig. 4, the step 220 specifically includes:
step 221: and acquiring the micro-motion signal with a first preset time length.
In this embodiment, the self-correlation function is used to determine the repetition rule of the inching signal in the time sequence, where the repetition rule is the similarity between the inching signal at this time and the inching signal after time shift. The first preset duration is a time shift variable in the autocorrelation function, and the first preset duration is set artificially and may be 10s, for example.
Step 222: and carrying out autocorrelation processing on the inching signal within the first preset time length to obtain an autocorrelation signal of the inching signal.
And the autocorrelation processing is to multiply and average the inching signal and the inching signal per se within the first preset time length to obtain an autocorrelation function of the inching signal, wherein the autocorrelation signal of the inching signal is the autocorrelation function of the inching signal. For example, the inching signal is x (t), thenThe autocorrelation function (autocorrelation signal) of which is Rx(τ) ═ x (t) x (t + τ) dt, where τ is the first predetermined period.
Step 223: and determining the maximum value of the peak value of the autocorrelation signal in the first preset time length.
Step 224: and if the maximum value of the peak value is greater than or equal to a preset threshold value, determining that the inching signal is a periodic signal.
The autocorrelation signal within the first preset duration is obtained and a plurality of peaks are searched out, so that the maximum value of the plurality of peaks within the first preset duration can be determined. It is understood that the peak may also be a peak located in the second half of the first preset time period, for example, when the first preset time period is 10s, a plurality of peaks of the autocorrelation signal in 5-10s are taken, and a peak maximum value is determined. Since the peak value of the autocorrelation function of the periodic signal is much larger than the peak value of the autocorrelation function of the aperiodic signal, the maximum value of the peak value of the autocorrelation signal within the first preset duration is compared with the preset threshold by setting the preset threshold. And if the maximum value of the peak value is greater than or equal to a preset threshold value, determining that the inching signal is a periodic signal.
In this embodiment, by establishing the autocorrelation signal, the periodicity of the inching signal can be accurately determined.
The signal energy of the micro-motion signal in unit time is the square sum of the amplitudes of all micro-motion signal sampling points in 1s, and can be obtained through the following formula:
wherein En is signal energy in unit time, i is the number of sampling points, n is the number of micro-motion signal sampling points in unit time, and x (i) is the amplitude of the micro-motion signal sampling points.
The preset energy threshold interval is an experience range which is artificially set according to actual experience. The lower limit of the preset energy threshold interval reflects the minimum value of the signal energy of the micro-motion signal in unit time, and if the signal energy of the micro-motion signal in unit time is smaller than the lower limit of the preset energy threshold interval, the target object is not on the bed. For example, when the target object leaves the bed, the fan continues to blow air against the bed, the micro-motion signal generated by the air flow is weak, and at this time, the micro-motion signal collected is weak and cannot reflect vital signs, so that the target object should be excluded.
The upper limit of the preset energy threshold interval reflects the maximum value of the signal energy of the micro-motion signal in unit time, if the signal energy of the micro-motion signal in unit time is larger than the upper limit of the preset energy threshold interval, the action amplitude of the target object exceeds the maximum value of the body action amplitude in the sleeping process, and the action corresponding to the micro-motion signal can be definitely determined to be generated when the micro-motion signal is not in sleep. For example, when the target object jumps in bed, the motion amplitude exceeds the maximum value of the body motion amplitude during sleep, and the micro-motion signal is collected too strongly and cannot be used as a valid signal, and therefore, the target object should be excluded.
That is, the micro-motion signals are filtered and screened through the preset energy threshold interval, so that the micro-motion signals which can effectively reflect sleep can be screened, namely the micro-motion signals with high reliability can be screened out, and the interference of other signals can be eliminated.
It should be noted that the upper limit and the lower limit of the preset energy threshold interval may be obtained through a large number of experiments, and may also be empirical values in the field.
Step 240: and determining the sign parameters of the target object according to the inching signals.
The sign parameters are parameters for reflecting the vital signs of the target object, the micro-motion signals reflect the vital signs (such as heartbeat, respiration and body movement), and the sign parameters can be determined by separating the micro-motion signals to separate signals corresponding to the vital signs.
In some embodiments, referring to fig. 5, the step 240 specifically includes:
step 241: and filtering the micro-motion signal to remove an interference signal in the micro-motion signal.
And filtering the micro-motion signal to filter an interference signal in the micro-motion signal, wherein the frequency of the interference signal can be set according to the actual situation.
In some embodiments, the filtering process includes a power frequency notch process, that is, a power frequency notch filter is used to filter a power frequency interference signal caused by the power system in the inching signal, for example, a power frequency interference signal of 50HZ or 60HZ in the inching signal is filtered.
Step 242: and performing band-pass filtering on the micro-motion signal after filtering processing by using a first preset frequency band to obtain a first micro-motion signal.
The first predetermined frequency band has a band frequency adapted to the band frequency of the signal generated by respiration, which covers all band frequencies of the signal generated by respiration, which is distinguishable from signals generated by other body signs (for example signals generated by heart rate or body movement), and which does not overlap, so that the signal generated by respiration can be separated. In this embodiment, the band frequency of the first predetermined frequency band is preferably 0.1HZ to 0.3HZ, but the band frequency of the first predetermined frequency band is not limited to 0.1HZ to 0.3HZ, and may be other band frequencies, such as 0.05HZ to 0.35 HZ.
And the micro-motion signal is subjected to band-pass filtering by the first preset frequency band and then outputs a first micro-motion signal, and the wave band frequency of the first micro-motion signal is within the wave band frequency of the first preset frequency band. The first micro-motion signal is a low-frequency steady-state signal which can reflect signals generated by respiration, so that physical sign parameters related to the respiration, such as respiration rate, can be accurately determined.
Step 243: and performing band-pass filtering on the micro-motion signal subjected to filtering processing by using a second preset frequency band to obtain a second micro-motion signal.
The band frequency of the second preset frequency band is greater than the band frequency of the first preset frequency band, and the band frequency of the second preset frequency band is not overlapped with the band frequency of the first preset frequency band.
The second predetermined frequency is adapted to the frequency of the signal generated by the heartbeat and the body movement, which covers all the frequency of the signal generated by the heartbeat and the body movement. The method is as follows. In this embodiment, the band frequency of the second predetermined frequency band is preferably 3HZ to 10HZ, but the band frequency of the second predetermined frequency band is not limited to 3HZ to 10HZ, and may be other band frequencies, such as 2HZ to 12 HZ.
And the micro-motion signal is subjected to band-pass filtering by the second preset frequency band and then outputs a second micro-motion signal, and the wave band frequency of the second micro-motion signal is within the wave band frequency of the second preset frequency band. The second jogging signal is a high-frequency steady-state signal and can reflect signals generated by heartbeat and body movement, so that physical sign parameters related to the heartbeat and the body movement, such as the heart rate and the body movement, can be accurately determined.
Step 244: and acquiring the signal quality of the first inching signal, and determining the first inching signal with the signal quality meeting the preset quality condition as a respiratory signal.
In this embodiment, after the signal quality evaluation is performed on the first inching signal, the first inching signal meeting the preset quality condition is screened out as a respiratory signal. The respiration signal is a micro-motion signal generated by respiration. The signal quality is a parameter for evaluating the quality of the signal, and can be set according to the characteristics of the signal.
For example, in this embodiment, the first inching signal is a periodic signal, and the signal quality is a standard deviation of signal peaks, that is, the quality of the respiration signal is determined by counting a plurality of peaks of the respiration signal over a period of time and calculating the standard deviation of the plurality of peaks of the respiration signal. Correspondingly, the preset quality condition is that the standard deviation is smaller than a preset standard deviation threshold value. Namely, the signal quality is evaluated through the dispersion of the respiration signal peak, and the smaller the dispersion of the respiration signal peak is, the better the signal quality is.
Step 245: and acquiring the signal quality of the second micro-motion signal, and determining that the second micro-motion signal with the signal quality meeting the preset quality condition is a heart rate and body motion mixed signal.
In this embodiment, after the second inching signal is subjected to signal quality evaluation, the second inching signal which meets the preset quality condition is screened out and is a heart rate and body motion mixed signal. The heart rate and body motion mixed signal is a micro-motion signal generated by respiration and body motion.
For example, in this embodiment, the second inching signal may be regarded as a periodic signal, and the signal quality is a standard deviation of signal peaks, that is, the quality of the heart rate and body motion mixed signal is determined by counting a plurality of peaks of the heart rate and body motion mixed signal over a period of time and calculating a standard deviation of the plurality of peaks of the heart rate and body motion mixed signal. Correspondingly, the preset quality condition is that the standard deviation is smaller than a preset standard deviation threshold value. Namely, the signal quality is evaluated through the dispersion of the heart rate body motion signal peak value, and the smaller the dispersion of the heart rate body motion signal peak value is, the better the signal quality is.
Step 246: and determining the sign parameters of the target object according to the heart rate and body motion mixed signals.
The sign parameters are parameters reflecting vital signs of the target subject. In some embodiments, the vital sign parameters include a state relative to a bed, a physical movement condition, a heart rate, and a respiration rate. It will be appreciated that the relative bed condition is one of in-bed and out-of-bed, and the physical movement condition is one of physical movement and non-physical movement. And determining the heart rate of the target object according to the respiration signal, and determining the state of the target object relative to a bed, the body movement condition of the target object and the heart rate according to the heart rate and body movement mixed signal.
Specifically, in some embodiments, referring to fig. 6, the step 246 includes:
step 2461: and acquiring the periodicity of the heart rate and body movement mixed signal in a second preset time length and the signal energy of the heart rate and body movement mixed signal in unit time in the second preset time length according to the respiration signal and the heart rate and body movement mixed signal.
The second preset time duration is longer than the first preset time duration, so that the periodicity of the heart rate and body motion mixed signal in the second preset time duration can also be determined by an autocorrelation signal of the heart rate and body motion mixed signal, which may specifically refer to steps 221 to 224, and is not described in detail herein. The signal energy of the heart rate and body motion mixed signal in the second preset time length in unit time can be obtained through the formula. It is understood that the second preset time period is an artificial empirical value, and can be determined by a large amount of experimental data as a critical value for determining the duration of the inching signal corresponding to the target object in the bed.
Step 2462: if the heart rate and body motion mixed signal in the second preset time period is determined to be an aperiodic signal according to the periodicity, and the signal energy of the heart rate and body motion mixed signal in unit time in the second preset time period is lower than the lower limit of the preset energy threshold interval, determining that the target object is in a bed leaving state in the second preset time period, otherwise, determining that the target object is in a bed leaving state in the second preset time period.
And in the second preset time period, if the heart rate and body motion mixed signal is an aperiodic signal and the signal energy of the heart rate and body motion mixed signal in unit time in the second preset time period is lower than the lower limit of the preset energy threshold interval, determining that the target object is in a bed leaving state in the second preset time period, otherwise, determining that the target object is in a bed in state in the second preset time period.
That is, if the heart rate and body motion mixed signal has no period within the second preset time period and the signal energy is low, it is determined that the target object is in the out-of-bed state within the second preset time period. And if the heart rate and body motion mixed signal has a period within the second preset time and the signal energy is strong, determining that the target object is in a bed state. Equivalently, if the heart rate and body motion mixed signal meets the condition: and if the period of the periodic signal is less than the lower limit of the preset energy threshold interval, and the duration of the period and the signal energy in the unit time meeting the conditions at the same time is longer than the second preset duration, determining that the target object is in a bed leaving state, otherwise, determining that the target object is in a bed state, thereby effectively avoiding misjudgment caused by the fact that the heart rate and body motion mixed signal does not meet the conditions in a short time.
In this embodiment, the state of the target object relative to the bed can be accurately determined by determining whether the target object is in or out of the bed through the period of the heart rate and the signal energy in the unit time and combining the preset second time length.
Step 2463: when the target object is in a bed state within the second preset time length, if the signal energy of the heart rate and body motion mixed signal within the second preset time length in unit time is greater than or equal to a first preset energy threshold value, determining that the target object generates body motion within the second preset time length, otherwise, determining that the target object does not generate body motion within the second preset time length.
The first preset energy threshold is the minimum value of signal energy in unit time of the heart rate and body movement mixed signal corresponding to the target object generating body movement. The first preset energy threshold may be set according to the actual condition of the target object, for example, when the weight of the target object is large, the first preset energy threshold should be correspondingly increased, and when the weight of the target object is light, for example, a child, the first preset energy threshold should be correspondingly decreased.
When the body movement occurs, the signal energy of the heart rate and body movement mixed signal in the unit time is increased from being smaller than the first preset energy threshold to the first preset energy threshold, when the signal energy of the heart rate and body movement mixed signal in the unit time is increased to the first preset energy threshold, the target object is determined to generate the body movement within the second preset time, and otherwise, the target object is determined not to generate the body movement within the second preset time.
Step 2464: when the target object does not generate body motion within the second preset time, determining the heart rate of the target object within the second preset time according to the heart rate and body motion mixed signal within the second preset time, and determining the breathing rate of the target object within the second preset time according to the breathing signal within the second preset time.
The heart rate is the number of beats per minute. Specifically, the number of peak values of the heart rate and body motion mixed signals in the second preset time period is calculated according to the heart rate and body motion mixed signals in the second preset time period, and the heart rate of the target object in the second preset time period can be converted according to the second preset time period and the number of peak values of the heart rate and body motion mixed signals in the second preset time period.
The respiration rate is the number of breaths per minute. Specifically, according to the respiration signals within the second preset time period, the peak value number of the respiration signals within the second preset time period is calculated, and according to the second preset time period and the peak value number of the respiration signals within the second preset time period, the respiration rate of the target object within the second preset time period can be converted.
When the target object does not generate body motion within the second preset time, the heart rate and the respiratory rate of the target object are calculated, so that the micro-motion signal generated by the body motion can be prevented from interfering the heart rate and the respiratory rate, and the accuracy of the heart rate and the respiratory rate is improved.
In some embodiments, the vital sign parameters further include a body movement type and a body movement duration, wherein the body movement type is one of a large body movement and a small body movement. Referring to fig. 7, the step 246 further includes:
step 2465: and when the target object generates body motion within the second preset time length, determining the time interval between the body motion starting point and the body motion stopping point as the body motion duration.
When body motion occurs, the signal energy of the heart rate and body motion mixed signal in unit time is increased to exceed the first preset energy threshold value and then is reduced to be lower than the first preset energy threshold value.
The body motion starting point is a time point when the signal energy of the heart rate and body motion mixed signal in unit time is increased from being smaller than the first preset energy threshold to the first preset energy threshold, and the body motion stopping point is a time point when the signal energy of the heart rate and body motion mixed signal in unit time is decreased from being larger than the first preset energy threshold to the first preset energy threshold.
Step 2466: and if the maximum value of the signal energy of the heart rate and body motion mixed signal in the unit time between the body motion starting point and the body motion stopping point is greater than or equal to a second preset energy threshold value, determining that the body motion type of the target object in the second preset time period is gross motion.
And the second preset energy threshold is the minimum value of the signal energy of the heart rate and body motion mixed signal in unit time when the target object generates body motion. The second preset energy threshold may be set according to the actual condition of the target object, for example, when the weight of the target object is large, the second preset energy threshold should be correspondingly increased, and when the weight of the target object is light, such as a child, the second preset energy threshold should be correspondingly decreased.
It can be understood that the signal energy per unit time of the heart rate and body motion mixed signal is positively correlated with the motion amplitude of the body motion. The signal energy of the heart rate and body motion mixed signals in unit time is related to the body motion amplitude at the corresponding moment, and the motion amplitude of the body motion is changed in one body motion process, so that if the signal energy of the heart rate and body motion mixed signals in unit time is larger than or equal to a second preset energy threshold value, the type of the body motion can be determined to be the gross motion, namely, the type of the body motion of the target object in the second preset time length is determined to be the gross motion.
Step 2467: and if the maximum value of the signal energy of the heart rate and body motion mixed signal in the unit time between the body motion starting point and the body motion stopping point is smaller than the second preset energy threshold value and larger than or equal to a third preset energy threshold value, determining that the body motion type of the target object in the second preset time period is small body motion.
And the third preset energy threshold is the minimum value of the signal energy of the heart rate and body motion mixed signal in unit time when the target object generates small body motion. The third preset energy threshold may be set according to the actual condition of the target object, for example, when the weight of the target object is large, the third preset energy threshold should be correspondingly increased, and when the weight of the target object is light, such as a child, the third preset energy threshold should be correspondingly decreased.
The method comprises the steps that signal energy in a plurality of heart rate and body motion mixed signals in unit time is included between the body motion starting point and the body motion stopping point, the magnitude of the signal energy in the heart rate and body motion mixed signals in unit time is related to body motion amplitude at corresponding moment, and in a body motion process, the motion amplitude of body motion is changed, so that if the maximum value of the signal energy in the heart rate and body motion mixed signals in unit time is smaller than the second preset energy threshold value and larger than or equal to the third preset energy threshold value, the type of body motion at this time is determined to be small body motion, namely the type of body motion of the target object in the second preset time is determined to be small body motion.
Step 250: and determining the sleep state of the target object according to the sign parameters.
The sleep state includes one of arousal, light sleep and deep sleep, and is used for representing the degree of falling asleep of the target object. The sleep state of the target subject may be determined based on the vital sign parameters, e.g., if a large body movement frequently occurs over a period of time, indicating that the target subject is awake or asleep.
In some embodiments, referring to fig. 8, the step 250 specifically includes:
step 251: if the number of times of the gross movement is smaller than a first preset threshold value in a third preset time period, the standard deviation of the heart rate is smaller than a first heart rate threshold value in the third preset time period, and the standard deviation of the respiration rate is smaller than a first respiration rate threshold value in the third preset time period, the sleep state is determined to be deep sleep.
And the third preset time length is greater than the second preset time length. The third preset time comprises a plurality of second preset times, and the third preset time is a time threshold for judging a sleep state. And when the physical sign parameter lasts for the third preset time, the sleep state can be determined. For example, in the third preset time period, the number of the body movements is small, and the dispersion of the heart rate and the respiration rate is small, then the deep sleep is determined.
Specifically, when the number of times of the body movement is smaller than a first preset threshold value in the third preset time period, the standard deviation of the heart rate is smaller than a first heart rate threshold value in the third preset time period, and the standard deviation of the respiration rate is smaller than a first respiration threshold value in the third preset time period, it is determined that the sleep state is deep sleep.
The first preset threshold is a threshold of the times of the body movement during deep sleep, that is, when the sleep state is deep sleep, the times of the body movement is greater than the first preset threshold. The first heart rate threshold is a threshold value of the standard deviation of the heart rate when the heart rate is in deep sleep, and the first respiration threshold is a threshold value of the standard deviation of the respiration rate when the heart rate is in deep sleep. That is, when the sleep state is deep sleep, the standard deviation of the heart rate is smaller than the first heart rate threshold, and the standard deviation of the respiration rate is smaller than the first respiration threshold. The first preset threshold, the first heart rate threshold and the first respiration threshold may be manually set actual experience values, or may be results after a large number of experiments.
Step 252: and if the number of times of the gross movement within a third preset time length is greater than the first preset threshold and less than a second preset threshold, determining that the sleep state is light sleep.
Step 253: and if the number of times of the gross movement within a third preset time length is greater than the second preset threshold value, determining that the sleep state is aroused.
The second preset threshold is a threshold of the number of times of the gross body movement in a shallow sleep, and it can be understood that the second preset threshold is larger than the first preset threshold. Namely, when the sleep state is light sleep, and the number of times of the gross movement is greater than the first preset threshold and less than the second preset threshold, determining that the sleep state is light sleep. Otherwise, if the number of the body movements in the third preset time length is larger than the second preset threshold value, determining that the sleep state is aroused.
In this embodiment, whether the inching signal is a periodic signal is determined by obtaining a inching signal of a target object, and when the inching signal is a periodic signal, further, whether signal energy in a unit time of the inching signal falls into a preset energy threshold interval is determined, if so, a physical sign parameter of the target object is determined according to the inching signal, and the sleep state of the target object can be accurately determined according to the physical sign parameter. That is, the jogging signals are screened according to the signal energy in periodicity and unit time, the jogging signals with high reliability are screened, and the interference of other signals can be effectively eliminated, so that the judgment accuracy is improved.
It should be noted that, in the foregoing embodiments, a certain order does not necessarily exist between the foregoing steps, and it can be understood by those skilled in the art from the description of the embodiments of the present invention that, in different embodiments, the foregoing steps may have different execution orders, that is, may be executed in parallel, may also be executed in an exchange manner, and the like.
The embodiment of the present invention further provides a sleep monitor 300, please refer to fig. 9, which includes a piezoelectric sensor 310 and a control processing module 320. The control processing module 320 is connected to the piezoelectric sensor 310.
The piezoelectric sensor 310 is configured to collect a micro-motion electrical signal, and the control processing module 320 is configured to process the micro-motion electrical signal to obtain a micro-motion signal.
The piezoelectric sensor 310 may be a strip-shaped piezoelectric film sensor. The piezoelectric sensor 310 may be placed on or under a mattress and directly under the armpit of the target object. When the target object lies on the bed, the body of the target object generates micro motion due to breathing, heartbeat and body movement, so that the piezoelectric sensor generates deformation, acquires micro motion electric signals and sends the micro motion electric signals to the control processing module. It is understood that the piezoelectric sensor 310 may have other forms and be placed elsewhere so long as it detects the micro-motion generated by the target object.
The control processing module 320 includes: at least one processor 321, and a memory 322 communicatively coupled to the at least one processor 321, for example, one processor in fig. 9. The memory 322 stores instructions executable by the at least one processor 321, and the instructions are executed by the at least one processor 321, so that the at least one processor 321 can perform the method for detecting a sleep state described in fig. 3 to 8.
The memory 322, which is a non-transitory computer readable storage medium, may be used for storing non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules corresponding to the method for detecting a sleep state in the embodiments of the present invention. The processor 321 may implement the method for detecting a sleep state described in fig. 3 to 8 by running the non-transitory software program, instructions and modules stored in the memory 322. In particular, the memory 322 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory may also include memory located remotely from the processor, which may be connected to the processor through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
Embodiments of the present invention also provide a non-transitory computer-readable storage medium storing computer-executable instructions, which are executed by one or more processors, such as one of the processors in fig. 9, so that the one or more processors can execute the method for detecting a sleep state in any of the method embodiments.
Embodiments of the present invention also provide a computer program product, which includes a computer program stored on a non-volatile computer-readable storage medium, where the computer program includes program instructions, which, when executed by an electronic device, cause the electronic device to execute any one of the methods for detecting a sleep state.
In summary, the method for detecting the sleep state judges whether the micro-motion signal is a periodic signal by obtaining the micro-motion signal of the target object, further judges whether the signal energy of the micro-motion signal in unit time falls into a preset energy threshold interval when the micro-motion signal is the periodic signal, determines the physical sign parameter of the target object according to the micro-motion signal if the signal energy of the micro-motion signal in unit time falls into the preset energy threshold interval, and can accurately determine the sleep state of the target object according to the physical sign parameter. That is, the jogging signals are screened according to the signal energy in periodicity and unit time, the jogging signals with high reliability are screened, and the interference of other signals can be effectively eliminated, so that the judgment accuracy is improved.
The above-described embodiments of the apparatus or device are merely illustrative, wherein the unit modules described as separate parts may or may not be physically separate, and the parts displayed as module units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network module units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a general hardware platform, and certainly can also be implemented by hardware. Based on such understanding, the above technical solutions substantially or contributing to the related art may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; within the idea of the invention, also technical features in the above embodiments or in different embodiments may be combined, steps may be implemented in any order, and there are many other variations of the different aspects of the invention as described above, which are not provided in detail for the sake of brevity; although the present 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 solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A method of detecting a sleep state, comprising:
acquiring a micro-motion signal of a target object, wherein the target object is an object relative to a bed;
judging whether the inching signal is a periodic signal or not;
if yes, judging whether the signal energy of the micro-motion signal in unit time falls into a preset energy threshold interval;
if yes, determining the physical sign parameters of the target object according to the micro-motion signal;
and determining the sleep state of the target object according to the sign parameters.
2. The method of claim 1, wherein said determining whether the inching signal is a periodic signal comprises:
acquiring the inching signal with a first preset time length;
performing autocorrelation processing on the inching signal within the first preset time length to obtain an autocorrelation signal of the inching signal;
determining the maximum value of the peak value of the autocorrelation signal within the first preset time length;
and if the maximum value of the peak value is greater than or equal to a preset threshold value, determining that the inching signal is a periodic signal.
3. The method according to claim 1, wherein said determining the vital sign parameters of the target subject from the micro-motion signal comprises:
filtering the micro-motion signal to remove an interference signal in the micro-motion signal;
performing band-pass filtering on the micro-motion signal after filtering processing by using a first preset frequency band to obtain a first micro-motion signal;
performing band-pass filtering on the micro-motion signal after filtering processing by using a second preset frequency band to obtain a second micro-motion signal, wherein the wave band frequency of the second preset frequency band is greater than the wave band frequency of the first preset frequency band, and the wave band frequency of the second preset frequency band is not overlapped with the wave band frequency of the first preset frequency band;
acquiring the signal quality of the first inching signal, and determining the first inching signal with the signal quality meeting a preset quality condition as a respiratory signal;
acquiring the signal quality of the second micro-motion signal, and determining that the second micro-motion signal with the signal quality meeting the preset quality condition is a heart rate and body motion mixed signal;
and determining the sign parameters of the target object according to the respiration signal and the heart rate and body movement mixed signal.
4. The method of claim 3, wherein the filtering process comprises a power frequency notching process.
5. The method of claim 3, wherein the signal quality is a standard deviation of a signal peak value, and wherein the predetermined quality condition is that the standard deviation is smaller than a predetermined standard deviation threshold.
6. The method of claim 3, wherein the vital sign parameters include relative to bed status, body movement, heart rate, and respiration rate;
the determining of the sign parameters of the target subject according to the respiration signal and the heart rate and body movement mixed signal comprises:
according to the heart rate and body movement mixed signal, acquiring the periodicity of the heart rate and body movement mixed signal within a second preset time length and the signal energy of the heart rate and body movement mixed signal within the second preset time length in unit time;
if the heart rate and body motion mixed signal in the second preset time length is determined to be an aperiodic signal according to the periodicity, and the signal energy of the heart rate and body motion mixed signal in unit time in the second preset time length is lower than the lower limit of the preset energy threshold interval, determining that the target object is in a bed leaving state in the second preset time length, otherwise, determining that the target object is in a bed in state in the second preset time length;
when the target object is in a bed state within the second preset time length, if the signal energy of the heart rate and body motion mixed signal within the second preset time length in unit time is greater than or equal to a first preset energy threshold value, determining that the target object generates body motion within the second preset time length, otherwise, determining that the target object does not generate body motion within the second preset time length;
when the target object does not generate body motion within the second preset time, determining the heart rate of the target object within the second preset time according to the heart rate and body motion mixed signal within the second preset time, and determining the breathing rate of the target object within the second preset time according to the breathing signal within the second preset time.
7. The method of claim 6, wherein the physical sign parameters further include a body movement type and a body movement duration, the body movement type being one of a large body movement and a small body movement;
the determining of the physical sign parameters of the target subject according to the respiration signal and the heart rate and body movement mixed signal further includes:
when the target object generates body motion within the second preset duration, determining a time interval between a body motion starting point and a body motion stopping point as body motion duration, wherein the body motion starting point is a time point when the signal energy in the heart rate and body motion mixed signal unit time is increased from being smaller than the first preset energy threshold value to the first preset energy threshold value, and the body motion stopping point is a time point when the signal energy in the heart rate and body motion mixed signal unit time is decreased from being larger than the first preset energy threshold value to the first preset energy threshold value;
if the maximum value of the signal energy of the heart rate and body motion mixed signal in the unit time between the body motion starting point and the body motion stopping point is larger than or equal to a second preset energy threshold value, determining that the body motion type of the target object in the second preset time length is general motion;
and if the maximum value of the signal energy of the heart rate and body motion mixed signal in the unit time between the body motion starting point and the body motion stopping point is smaller than the second preset energy threshold value and larger than or equal to a third preset energy threshold value, determining that the body motion type of the target object in the second preset time period is small body motion.
8. The method of claim 7, wherein the sleep state is one of wakefulness, light sleep, and deep sleep;
the determining the sleep state of the target object according to the sign parameters comprises:
if the number of times of the body movement within a third preset time period is smaller than a first preset threshold, the standard deviation of the heart rate within the third preset time period is smaller than a first heart rate threshold, and the standard deviation of the respiration rate within the third preset time period is smaller than a first respiration rate threshold, determining that the sleep state is deep sleep, wherein the third preset time period is longer than a second preset time period;
if the number of times of the gross movement within a third preset time length is greater than the first preset threshold and less than a second preset threshold, determining that the sleep state is light sleep;
and if the number of times of the gross movement within a third preset time length is greater than the second preset threshold value, determining that the sleep state is aroused.
9. A sleep monitor, comprising:
the piezoelectric sensor is used for acquiring a micromotion electric signal;
the control processing module, the control processing module with piezoelectric sensor is connected, the control processing module is used for to the fine motion signal of telecommunication handles to acquire the fine motion signal, the control processing module includes:
at least one processor, and
a memory communicatively coupled to the at least one processor, wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any of claims 1-8.
10. A non-transitory computer readable storage medium having stored thereon computer executable instructions which, when executed by a sleep monitor, cause the sleep monitor to perform the method of any one of claims 1-8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010723356.3A CN111938588A (en) | 2020-07-24 | 2020-07-24 | Method for detecting sleep state, sleep monitor and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010723356.3A CN111938588A (en) | 2020-07-24 | 2020-07-24 | Method for detecting sleep state, sleep monitor and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111938588A true CN111938588A (en) | 2020-11-17 |
Family
ID=73338833
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010723356.3A Pending CN111938588A (en) | 2020-07-24 | 2020-07-24 | Method for detecting sleep state, sleep monitor and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111938588A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113159505A (en) * | 2021-03-15 | 2021-07-23 | 海尔(深圳)研发有限责任公司 | Method, device, platform equipment and system for monitoring sleep instrument |
| CN113679345A (en) * | 2021-08-13 | 2021-11-23 | 珠海格力电器股份有限公司 | Sleep monitoring method, device and system and storage medium |
| CN114027799A (en) * | 2021-12-13 | 2022-02-11 | 珠海格力电器股份有限公司 | Method and device for determining time point of falling asleep |
| CN116649917A (en) * | 2023-07-24 | 2023-08-29 | 北京中科心研科技有限公司 | Sleep quality monitoring method and device and wearable equipment |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103142219A (en) * | 2013-03-28 | 2013-06-12 | 江苏晓山信息产业股份有限公司 | Unrestraint type vital sign monitoring mattress |
| CN107550484A (en) * | 2017-09-28 | 2018-01-09 | 漫迪医疗仪器（上海）有限公司 | A kind of mcg-signalses quality evaluating method and system |
| CN107898432A (en) * | 2017-10-17 | 2018-04-13 | 深圳和而泰智能控制股份有限公司 | Sound of snoring detection method, device, equipment and medium |
| CN107951470A (en) * | 2017-12-12 | 2018-04-24 | 深圳市迈迪加科技发展有限公司 | Sleep signal processing method and processing device |
| CN108042108A (en) * | 2017-12-06 | 2018-05-18 | 中国科学院苏州生物医学工程技术研究所 | A kind of sleep quality monitoring method and system based on body shake signal |
| CN108697348A (en) * | 2018-03-16 | 2018-10-23 | 深圳和而泰数据资源与云技术有限公司 | A kind of physiologic information monitoring method and physiologic information monitoring pad, a kind of mattress |
| CN109907729A (en) * | 2018-10-12 | 2019-06-21 | 中科传感技术(青岛)研究院 | The detection method of vital signs when a kind of sleep |
| CN111035367A (en) * | 2019-12-31 | 2020-04-21 | 华南师范大学 | Signal detection method and system for judging sleep apnea |
| CN111281349A (en) * | 2020-03-12 | 2020-06-16 | 北京曙光易通技术有限公司 | Sleep disordered breathing monitoring method and system |
| CN111407315A (en) * | 2020-03-24 | 2020-07-14 | 浙江大学温州研究院 | Quality evaluation method for ultrasonic Doppler fetal heart signals |
-
2020
- 2020-07-24 CN CN202010723356.3A patent/CN111938588A/en active Pending
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103142219A (en) * | 2013-03-28 | 2013-06-12 | 江苏晓山信息产业股份有限公司 | Unrestraint type vital sign monitoring mattress |
| CN107550484A (en) * | 2017-09-28 | 2018-01-09 | 漫迪医疗仪器（上海）有限公司 | A kind of mcg-signalses quality evaluating method and system |
| CN107898432A (en) * | 2017-10-17 | 2018-04-13 | 深圳和而泰智能控制股份有限公司 | Sound of snoring detection method, device, equipment and medium |
| CN108042108A (en) * | 2017-12-06 | 2018-05-18 | 中国科学院苏州生物医学工程技术研究所 | A kind of sleep quality monitoring method and system based on body shake signal |
| CN107951470A (en) * | 2017-12-12 | 2018-04-24 | 深圳市迈迪加科技发展有限公司 | Sleep signal processing method and processing device |
| CN108697348A (en) * | 2018-03-16 | 2018-10-23 | 深圳和而泰数据资源与云技术有限公司 | A kind of physiologic information monitoring method and physiologic information monitoring pad, a kind of mattress |
| CN109907729A (en) * | 2018-10-12 | 2019-06-21 | 中科传感技术(青岛)研究院 | The detection method of vital signs when a kind of sleep |
| CN111035367A (en) * | 2019-12-31 | 2020-04-21 | 华南师范大学 | Signal detection method and system for judging sleep apnea |
| CN111281349A (en) * | 2020-03-12 | 2020-06-16 | 北京曙光易通技术有限公司 | Sleep disordered breathing monitoring method and system |
| CN111407315A (en) * | 2020-03-24 | 2020-07-14 | 浙江大学温州研究院 | Quality evaluation method for ultrasonic Doppler fetal heart signals |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113159505A (en) * | 2021-03-15 | 2021-07-23 | 海尔(深圳)研发有限责任公司 | Method, device, platform equipment and system for monitoring sleep instrument |
| CN113679345A (en) * | 2021-08-13 | 2021-11-23 | 珠海格力电器股份有限公司 | Sleep monitoring method, device and system and storage medium |
| CN113679345B (en) * | 2021-08-13 | 2022-06-14 | 珠海格力电器股份有限公司 | Sleep monitoring method, device and system and storage medium |
| CN114027799A (en) * | 2021-12-13 | 2022-02-11 | 珠海格力电器股份有限公司 | Method and device for determining time point of falling asleep |
| CN114027799B (en) * | 2021-12-13 | 2023-03-14 | 珠海格力电器股份有限公司 | Method and device for determining time point of falling asleep |
| CN116649917A (en) * | 2023-07-24 | 2023-08-29 | 北京中科心研科技有限公司 | Sleep quality monitoring method and device and wearable equipment |
| CN116649917B (en) * | 2023-07-24 | 2023-10-24 | 北京中科心研科技有限公司 | Sleep quality monitoring method and device and wearable equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111938588A (en) | Method for detecting sleep state, sleep monitor and storage medium | |
| JP7000342B2 (en) | Prediction and monitoring of urination | |
| US10706717B2 (en) | Electronic device and control method thereof | |
| CN111938584B (en) | Sleep monitoring method and equipment | |
| JP5552853B2 (en) | Biological information measuring device, biological information measuring method, and biological information measuring program | |
| JP5496137B2 (en) | Sleep state detection device, air conditioner using the same, sleep state detection method, and air conditioner control method | |
| CN104323766A (en) | Autoreflection heart rate detector | |
| CN108697348A (en) | A kind of physiologic information monitoring method and physiologic information monitoring pad, a kind of mattress | |
| CN101835178B (en) | Method for realizing remote wireless monitoring and wireless monitoring device | |
| US20160183880A1 (en) | Biological information measuring device and driving control method of the same | |
| CN208876492U (en) | A kind of physiologic information monitoring pad and mattress | |
| TWI643041B (en) | Smart system and method for controlling alarm | |
| EP3316765A1 (en) | Sleep monitoring | |
| KR20170028903A (en) | Methods and systems for reducing energy consumption of a heart rate monitor | |
| CN104122864A (en) | System for detecting human body status and capable of controlling household appliance through human body status | |
| CN109373391B (en) | Wind speed adjusting method and device, range hood, air purifier and storage medium | |
| CN111988424A (en) | Intelligent sleep monitoring bed, system and method | |
| CN108375909A (en) | A kind of parameters analysis method, device, equipment and computer readable storage medium | |
| CN112451834A (en) | Sleep quality management method, device, system and storage medium | |
| CN109524117A (en) | Establish the method and electronic device of the personal blood pressure estimation model of specific user | |
| CN111726271B (en) | Electrical equipment configuration method under night condition and intelligent home system | |
| Han et al. | Smart sleep care system for quality sleep | |
| JP2014195710A (en) | Biological information measuring apparatus, biological information measuring method, and biological information measuring program | |
| US20210121657A1 (en) | Method for determining the risk of a user waking up in an undesirable state | |
| JP7279812B2 (en) | STRESS ESTIMATION DEVICE, OPERATION METHOD OF STRESS ESTIMATION DEVICE, AND PROGRAM |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |