WO2018049852A1

WO2018049852A1 - Sleep evaluation method, apparatus and system

Info

Publication number: WO2018049852A1
Application number: PCT/CN2017/087499
Authority: WO
Inventors: 蔡洁凌; 黄建新; 李明; 戴鹏; 沈劲鹏; 陈祯坤; 黄锦锋
Original assignee: 深圳市迈迪加科技发展有限公司
Priority date: 2016-09-13
Filing date: 2017-06-07
Publication date: 2018-03-22
Also published as: CN106419841A

Abstract

Disclosed are a sleep evaluation method, apparatus and system. Besides determining sleeping state information according to an obtained sleep monitoring signal, the factors which influence sleep are also added for the evaluation. The evaluation parameters are more diverse, comprehensive and a sleep evaluation result will be more accurate. The method comprises: according to an obtained sleep monitoring signal, determining sleeping state information (101); according to one or more among the obtained environment monitoring signal, a body state detection result, a movement record, a food intake record and a mentality record, determining sleep influence information (102); and according to the sleeping state information and the sleep influence information, evaluating sleep quality and obtaining a sleep evaluation result (103).

Description

Sleep evaluation method, device and system

cross reference

The present application is hereby incorporated by reference in its entirety in its entirety in its entirety in its entirety in the the the the the the the the the the

Technical field

The present invention relates to the field of sleep monitoring technology, and in particular to a sleep evaluation method, apparatus and system.

Background technique

Good sleep can alleviate and relieve mental stress, ensure normal metabolism of the human body, accelerate the healing of damaged tissues, and make the functions and mental psychology of various organs of the human body in good condition. Conversely, lack of sleep can lead to memory loss, decreased concentration, fatigue, and even depression and mental disorders. Therefore, the quality of sleep directly affects people's quality of life.

Most of the sleep monitoring products currently on the market use the following technical solutions to assess sleep quality:

1. Use the acceleration sensor and/or gyroscope to monitor the vibration, and use simple body movement as the sleep monitoring parameter.

2. Use a piezoelectric or pressure sensor to monitor heart rate, respiration rate, and vibration, and assess sleep quality based on monitored heart rate, respiration rate, and vibration.

3. Use radar to detect the movements of the chest and the chest during breathing to assess the quality of sleep.

In summary, in the prior art, the monitoring information is less, the sleep parameters are evaluated, and the accuracy of the evaluation is affected.

Summary of the invention

In view of this, the technical problem to be solved by the present invention is to provide a sleep evaluation method, device and system to improve evaluation accuracy.

In order to solve the above technical problem, the present invention discloses a sleep evaluation method, including:

Determining sleep state information according to the acquired sleep monitoring signal, wherein the sleep monitoring signal is generated by monitoring a physical sign of the subject under sleep;

Determining sleep impact information according to one or more of the obtained environmental monitoring signals, physical condition detection results, exercise records, diet records, and psychological records;

Based on the sleep state information and the sleep influence information, the sleep quality is evaluated and a sleep evaluation result is obtained.

Optionally, in the sleep evaluation method, the sleep state information includes at least one sleep state information item, and the sleep influence information includes at least one sleep influence information item;

Correspondingly, the assessing the sleep quality according to the sleep state information and the sleep influence information, and obtaining a sleep assessment result, includes:

Obtaining, according to a correspondence between the preset sleep state information item and the scoring coefficient, a scoring coefficient corresponding to each of the sleep state information items in the sleep state information;

Acquiring a scoring coefficient corresponding to each of the sleep influence information items in the sleep influence information according to a correspondence between a preset sleep influence information item and a scoring coefficient;

Evaluating sleep quality and obtaining sleep assessment results based on all of the obtained scoring coefficients;

The sleep state information item is analyzed according to a signal resolution policy corresponding to the preset state score item, and the sleep monitoring information is obtained; and the sleep influence information item is determined based on a preset impact score item.

Optionally, in the sleep evaluation method, the determining the sleep quality and obtaining the sleep evaluation result according to all the obtained scoring coefficients, including:

Adding all of the obtained scoring coefficients, and the obtained sum is taken as the sleep evaluation result; or

Deducting all of the scoring coefficients from the preset base score, and obtaining the difference as the sleep evaluation result; or

Obtaining a weight corresponding to each of the scoring coefficients, and performing weighted summation on all the obtained scoring coefficients, and obtaining a weighted sum as the sleep evaluation result; or

All the obtained scoring coefficients are used as input parameters of the preset evaluation strategy, and the sleep evaluation result is obtained according to the preset evaluation strategy.

Optionally, the sleep assessment method described above further includes:

Obtaining an evaluation level corresponding to the score interval of the sleep evaluation result according to a correspondence between the preset score interval and the evaluation level, and using the evaluation level as the sleep evaluation result.

Optionally, the sleep assessment method described above further includes:

The sleep assessment results are displayed and/or broadcasted.

Optionally, the sleep assessment method described above further includes:

And analyzing the sleep state information and the sleep influence information to generate sleep suggestion information;

The sleep suggestion information is displayed and/or broadcasted.

The invention also discloses a sleep evaluation device, comprising:

a first determining module, configured to determine sleep state information according to the acquired sleep monitoring signal, wherein the sleep monitoring signal is generated by monitoring a physical sign of the measured subject in a sleep state;

a second determining module, configured to determine sleep impact information according to one or more of the obtained environmental monitoring signals, physical condition detection results, exercise records, diet records, and psychological records;

And an evaluation module, configured to evaluate sleep quality according to the sleep state information and the sleep influence information, and obtain a sleep evaluation result.

Optionally, in the above sleep evaluation device, the sleep state information includes at least one sleep state information item, and the sleep influence information includes at least one sleep influence information item;

Correspondingly, the evaluation module comprises:

a first acquiring unit, configured to acquire a scoring coefficient corresponding to each of the sleep state information items in the sleep state information according to a correspondence between a preset sleep state information item and a scoring coefficient;

a second acquiring unit, configured to acquire a scoring coefficient corresponding to each of the sleep influence information items in the sleep influence information according to a correspondence between a preset sleep influence information item and a scoring coefficient;

a determining unit, configured to evaluate sleep quality according to all the obtained scoring coefficients and obtain a sleep evaluation result;

Optionally, in the above sleep evaluation device, the determining unit is specifically configured to:

Adding all the obtained scoring coefficients, and the obtained sum is taken as the sleep evaluation result; or

All the obtained scoring coefficients are used as input parameters of the preset evaluation strategy to obtain the sleep evaluation result.

Optionally, the above sleep evaluation device further includes:

The obtaining module is configured to obtain an evaluation level corresponding to the score interval of the sleep evaluation result according to the correspondence between the preset score interval and the evaluation level.

Optionally, the above sleep evaluation device further includes:

A first display and/or broadcast module for displaying and/or broadcasting the sleep assessment result.

Optionally, the above sleep evaluation device further includes:

a generating module, configured to analyze the sleep state information and the sleep impact information, and generate sleep suggestion information;

a second display and/or broadcast module for displaying and/or broadcasting the sleep suggestion information.

The invention also discloses a sleep evaluation system, comprising:

At least one first sensor for monitoring signs of the subject under sleep and generating a corresponding sleep monitoring signal;

At least one second sensor for monitoring a sleeping environment and generating a corresponding environmental monitoring signal, a measuring instrument for detecting physiological parameters of the measured body, and a motion monitor for monitoring and recording motion information of the measured body And one or more of a recording device for recording dietary information input by the user and an evaluation device for assessing the mental health of the user;

a processor, configured to determine sleep state information according to the acquired sleep monitoring signal; determine sleep influence according to one or more of the obtained environmental monitoring signal, physical condition detection result, exercise record, diet record, and psychological record Information; evaluating sleep quality based on the sleep state information and the sleep effect information and obtaining a sleep evaluation result.

Optionally, the above sleep evaluation system further includes: a client device; wherein the processing The processor is a processor built into the client device.

Optionally, in the above sleep evaluation system, the client device is provided with a display screen for displaying the sleep evaluation result and/or an audio output device for broadcasting the sleep evaluation result.

Optionally, in the above sleep assessment system, the client device is a mobile phone, a tablet computer, a notebook computer, a desktop computer, a television, a wearable electronic device, or a voice device.

Compared with the prior art, the technical solution provided by the embodiment of the present invention not only determines the sleep state information according to the acquired sleep monitoring signal, but also affects the sleep factor to be evaluated, and the evaluation parameter is more comprehensive and comprehensive, and the sleep evaluation result is more accurate.

DRAWINGS

The drawings described herein are intended to provide a further understanding of the invention, and are intended to be a part of the invention. In the drawing:

1 is a schematic flow chart of a sleep evaluation method according to an embodiment of the present invention;

2 is a schematic flowchart of another sleep evaluation method according to an embodiment of the present invention;

FIG. 3 is a diagram showing an example of displaying sleep evaluation results according to an embodiment of the present invention; FIG.

FIG. 4 is a diagram showing another example of displaying sleep evaluation results according to an embodiment of the present invention; FIG.

FIG. 5 is a schematic structural diagram of a sleep evaluation apparatus according to an embodiment of the present invention; FIG.

FIG. 6 is a schematic structural diagram of a sleep evaluation system according to an embodiment of the present invention.

detailed description

The technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. It is a partial embodiment of the invention, and not all of the embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts are within the scope of the present invention.

FIG. 1 is a schematic flowchart diagram of a sleep evaluation method according to an embodiment of the present invention. The execution body of the method provided by the embodiment of the present invention may be a sleep evaluation device, and the device may be a set A hardware having an embedded program on the terminal, which may be an application software installed in the terminal, or a tool software embedded in the terminal operating system, is not limited in the embodiment of the present invention. The terminal can be any terminal device including a mobile phone, a tablet computer, a PDA (Personal Digital Assistant), a notebook computer, a desktop computer, and the like. Specifically, as shown in FIG. 1 , the method provided in this embodiment includes:

Step 101: Determine sleep state information according to the acquired sleep monitoring signal.

Wherein, the sleep monitoring signal is generated by monitoring signs of the subject under sleep. Specifically, the sleep monitoring signal may include at least one of a body motion signal, a sleep heart rate signal, a sleep breathing rate signal, a respiratory sound signal, a brain wave signal, an eye wave signal, a myoelectric wave signal, and the like. For example, the body motion signal can be monitored by an acceleration sensor and/or a gyroscope. For another example, the piezoelectricity or the pressure sensor is used to monitor the heart rate, the respiratory rate, the body motion, and the like of the subject under sleep; the radar is used to detect the undulating state of the chest when the subject is in a sleep state and the body is in a state of breathing; The receiving sensor collects the respiratory sound signal; the electric wave sampling sensor is used to collect the brain wave signal, the eye wave signal and the myoelectric wave signal. Specifically, the embodiment of the present invention does not specifically limit which sensor is used for monitoring/acquisition of each signal. The execution subject sleep evaluation device of the method provided by the embodiment can obtain a sleep monitoring signal from each sensor and/or monitoring instrument through a serial port, a wireless network, a limited data line, and the like in the device.

For example, in a specific implementation example of the embodiment of the present invention, the sleep monitoring signal may be a piezoelectric sensor (such as a piezoelectric film, a thin film line switch), a pressure sensor (such as a hydraulic pressure, a pneumatic pressure, etc.), a microphone, a capacitor, and an electric wave. The sampling sensor monitors; the piezoelectric sensor (such as piezoelectric film), the pressure sensor (such as hydraulic pressure, air pressure, etc.) and the disturbance signal in the signal detected by the capacitance are recognized as body motion signals, and then the signals in different frequency bands are separated. Further, a sleep heart rate signal and a sleep respiration rate signal are obtained by a signal processing method. The separation method may adopt various methods in the prior art, such as time domain analysis, frequency domain analysis, time-frequency analysis, and the like. The microphone monitors the respiratory sound signal; the radio wave sampling sensor collects the brain wave signal, the eye wave signal, and the myoelectric wave signal.

It should be noted that the sleep monitoring signal obtained in the embodiment of the present invention may be a real-time monitoring signal or a non-real-time monitoring signal.

In an achievable solution, the embodiment of the present invention may analyze the sleep monitoring signal one by one according to a signal resolution policy corresponding to each rating item based on at least one preset state score item, and obtain sleep corresponding to each rating item. Status information item. That is, the sleep state information may include at least one sleep Sleep status information item. In this embodiment, the sleep state information item includes at least one of the following categories:

1. Information about sleep state information about heart rate, such as: slow heart rate, heart rate, heart rate disorder (referring to heartbeat or fast or slow, exceeding the general range), heart rate overspeed, number of heartbeat pauses, etc.;

2, sleep state information items related to respiratory rate, such as: breathing rate, breathing rate, breathing slowness, number of apneas, and so on.

3. Sleep status information items related to sleep time, such as: bedtime, wake-up time, sleep time, sleep time (actual sleep time), deep sleep ratio, sleep duration (based on bedtime and wake-up time) Calculated), REM (Rapid Eye Movement) ratio, non-REpid Eye Movement ratio (NREM (Non-Rapid Eye Movement) ratio), non-REM sleep 1 period, non-rapid eye movement The duration of sleep 2, the duration of non-rapid eye movement sleep 3, the duration of non-rapid eye movement sleep 4, and so on.

What needs to be explained here is that during the period of sleep, the brain wave frequency becomes faster and the amplitude becomes lower. At the same time, it also shows the heart rate is faster, the blood pressure is increased, the muscles are slack, and the eyeball keeps swinging. Sleep, called rapid eye movement sleep, is also called heterophasic sleep, and some people call it active sleep. Other sleeps other than rapid eye movements are called slow wave sleep, also known as quiet sleep, that is, non-rapid eye movement sleep, in which slow wave sleep is divided into phase 1 (sleeper), phase 2 (light sleep) ), stage 3 (moderate sleep period), stage 4 (deep sleep period). Therefore, the proportion of rapid eye movement sleep refers to the ratio of the duration of rapid eye movement sleep to the length of sleep, and the proportion of non-rapid eye movement sleep (NREM ratio) refers to stage 1 (sleeping period), stage 2 (shallow sleep period), stage 3 ( The proportion of sleep duration in the middle sleep period and the fourth stage (deep sleep period).

4. Information about sleep state information such as wake-up time, wake-up time, wake-up time, number of bed departures, time to bed, length of bed departure, body movement and number of turns, and so on.

An achievable method of the embodiment of the present invention: obtaining a plurality of sleep state information items related to a sleep heart rate according to the sleep heart rate signal. For example, determining the heart rate according to the sleep heart rate signal (ie, the average frequency of the sleep heart rate signal as the heart rate of the subject); determining whether the heart rate is slow or the sleep state information item by determining whether the heart rate is less than the preset heart rate threshold; determining whether the heart rate is greater than Presetting a heart rate threshold to determine a heart rate overspeed sleep state information item; determining, according to a frequency range of the sleep heart rate signal, whether there is a heart rate irregularity sleep state information item; according to the sleep heart rate signal, there is no abnormality of the heartbeat signal (having breathing Signal) Determine the number of heartbeat pauses.

An achievable method of the embodiment of the present invention: obtaining a sleep state information item related to a breathing rate according to a sleep breathing rate signal. For example, the respiratory rate is determined according to the sleep respiration rate signal (ie, the average frequency of the sleep respiration rate signal is taken as the respiration rate of the subject); the sleep state information item is determined by determining whether the respiration rate is less than the preset respiration rate threshold. The sleep state information item of the over-speed is determined by determining whether the respiration rate is greater than the preset respiration rate threshold; and the number of apneas is determined according to the abnormal number of non-respiratory signals (with a heartbeat signal) in the sleep respiration rate signal.

An achievable method of the embodiment of the present invention combines at least one of an electroencephalogram signal, an electroencephalogram signal, and an electromyogram signal, and at least one of a body motion signal, a sleep heart rate signal, and a sleep respiration rate signal. After the overall analysis, the sleep state information item related to the sleep time is obtained. For example, the sleep duration is determined according to the start and stop time of the sleep monitoring signal; when the frequency of the sleep heart rate signal and/or the respiratory rate signal is lower than a set threshold, the time point (which is the actual sleep time point) is recorded, and the sleep monitoring is performed. The start time of the signal and the time point determine the length of sleep; of course, there are many ways to determine the method of falling asleep, for example, by heart rate and / or respiratory rate and / or body motion times below a set threshold, or by brain wave signals And/or the electric wave of the ocular wave signal and/or the myoelectric signal analyzes the sleep state, thereby obtaining the actual sleep time point; according to the body motion signal, the sleep heart rate signal, the sleep respiration rate signal, the brain wave signal, the ocular wave signal and the muscle The electrical signal determines whether the subject is in deep sleep, and if so, records the length of time the subject is in deep sleep, and determines the proportion of deep sleep according to the length of the deep sleep and the length of sleep. Similarly, according to the body motion signal, sleep heart rate signal, sleep respiration rate signal, brain wave signal, eye wave signal and myoelectric signal, it can be judged whether the measured body is in the rapid eye movement period, and if so, the measured object is in the fast eye. The duration of the exercise period, the proportion of rapid eye movement sleep (REM ratio) is determined according to the duration of the rapid eye movement period and the length of sleep; the ratio of non-rapid eye movement sleep (NREM ratio), the duration of non-rapid eye movement sleep, non-rapid eye movement The duration of sleep 2, the duration of non-rapid eye movement sleep, and the duration of non-rapid eye movement sleep can also be achieved by a similar method, which will not be described in detail here. It should be noted that the analysis method of each signal in the embodiment of the present invention may be implemented by using various technologies in the prior art, and is not specifically limited herein.

An achievable method of the embodiment of the present invention: obtaining a sleep state information item related to body motion according to a body motion signal. For example, depending on the number of times the signal is not input in the body motion signal, or the number of times the signal input is not present in the sleep heart rate signal and the sleep respiration rate signal, the number of times of leaving the bed is determined; or the pressure can be obtained by the piezoelectric sensor during the sleep time. Signaling, and analyzing the number of times the signal input does not exist in the pressure signal as the number of times of leaving the bed; determining whether the number of awake times is based on whether the frequency of the sleep heart rate signal and/or the sleep breathing rate signal is higher than a preset threshold, and of course, the number of awake times Can pack Including: body movements and turning times, number of beds, and so on.

The foregoing provides a method for determining each sleep state information item in the sleep state information. Of course, each of the sleep state information items is not limited to only adopting the foregoing determining method, and other determining strategies may be used to obtain corresponding information items. I will not list them one by one here.

Step 102: Determine sleep impact information according to one or more of the obtained environmental monitoring signals, physical condition detection results, exercise records, diet records, and psychological records.

The environmental monitoring signal may include at least one of a temperature monitoring signal, a humidity monitoring signal, a light intensity monitoring signal, a noise monitoring signal, a carbon dioxide concentration monitoring signal, and an inhalable particulate matter monitoring signal. The temperature monitoring signal can be obtained by monitoring the temperature sensor; the humidity monitoring signal can be obtained by the humidity sensor; the light intensity monitoring signal can be obtained by the light sensor; the noise monitoring signal can be obtained by the noise sensor; and the carbon dioxide concentration monitoring signal can be obtained by monitoring the carbon dioxide concentration sensor; Inhalable particulate matter (eg PM2.5) monitoring signals can be monitored by a respirable particulate sensor.

The body condition test results may include blood oxygen saturation, blood pressure, blood sugar, and the like. Oxygen saturation can be measured by the measurement method of the finger-type photoelectric sensor. The measurement only needs to be placed on the human finger, using the finger as a transparent container for hemoglobin, using red light with a wavelength of 660 nm and near-infrared light of 940 nm. As the incident light source, the light transmission intensity through the tissue bed was measured to calculate the hemoglobin concentration and the blood oxygen saturation. Of course, the blood oxygen saturation can also be detected by other methods, which is not specifically limited in the embodiment of the present invention. In addition, blood pressure and blood sugar can be detected by using corresponding instruments in the prior art, and will not be described herein.

Motion recording can be obtained by an acceleration sensor or a gyroscope. Among them, the acceleration sensor or gyroscope can be placed in devices such as wearable devices (such as electronic wristbands, watches), pedometers, and mobile phones. Among them, the motion record includes a motion type record, a motion duration record, a motion amount record, and a motion time period record. Among them, the motion type record can be input by the user through the user interface or default to running, brisk walking, jump counting and the like. When the type of exercise is instrument exercise or yoga, etc., the user is required to input the sport type name through the user interface or select a corresponding option or program in the user interface to automatically determine the type of exercise. The motion duration record can be determined based on the recorded motion start time and the motion end time. If the user's exercise type is running, the exercise amount can be obtained according to the exercise duration and the exercise distance; if the user's exercise type is the instrument exercise, the exercise amount can be obtained according to the exercise duration and the preset first coefficient and the exercise duration; if the user's exercise type is yoga The amount of exercise can be obtained according to the preset second coefficient and the length of exercise. and many more. It should be noted here that for a type of motion that cannot count distances and counts, a coefficient can be set for such a type of motion in advance, based on which the types of motions that cannot be counted, such as yoga and instrument movement, can be quantified. Of course, for motion types that cannot be counted by quantity, it is also possible to quantify only based on the exercise time.

Dietary records can be obtained from dietary information entered by the user. For example, the user can input a specific eating time, the type and amount of food ingested, and the like through the user interface, wherein the eating time may be input by the user, or may be based on a trigger button or an application installed in the user's touch user interface ( The physical button on the client device of APP) starts counting until the end of the trigger. The user interface may be a web interface or a user interface of an application (APP) installed on the client device. Alternatively, the type and amount of food may be obtained by scanning or/and metering by a client or other electronic device.

Similarly, psychological records can also be obtained through mood information entered by the user. For example, the user can input the mood content through the user interface or select the corresponding psychological condition through the option; or the psychological record can also be obtained through the psychological test answer sheet submitted by the user.

In one possible implementation, the sleep impact information includes at least one sleep impact information item. Embodiments of the present invention may determine a sleep impact information item based on at least one predetermined impact score item. The predetermined impact score item may include: temperature parameter, humidity parameter, light intensity, noise, carbon dioxide concentration, inhalable particulate matter concentration, exercise law, diet rule, mental health degree, and the like. Correspondingly, the foregoing step 102 determines sleep impact information according to one or more of the obtained environmental monitoring signals, physical condition detection results, exercise records, diet records, and psychological records, which may be specifically:

Determining temperature parameters based on the acquired temperature monitoring signals; and/or

Determining the humidity parameter based on the acquired humidity monitoring signal; and/or

Determining the light intensity based on the acquired light intensity monitoring signal; and/or

Determining noise based on the acquired noise monitoring signal; and/or

Determining the carbon dioxide concentration based on the acquired carbon dioxide concentration monitoring signal; and/or

Determining the concentration of inhalable particulate matter based on the acquired monitoring signal of inhalable particulate matter (eg PM2.5); and/or

Determine the blood oxygen saturation, blood pressure, and/or blood glucose in the obtained physical condition test result as Sleep affecting information items in sleep impact information; and/or

According to a preset time period (such as nearly one month) in the motion record or the duration of the exercise, the amount of exercise, the type of exercise, etc., the motion law is statistically analyzed; and/or

Analyze the pattern of diet based on a pre-set time period (eg, nearly one week) in the diet record or on the day's dietary record; and/or

At least one of mental health, for example, degree of stress, degree of anxiety, degree of fatigue, degree of grief, degree of depression, etc., is analyzed based on a recorded time period in the psychological record or the recorded content of the day.

It can be seen from the above that the sleep influence information may include at least one sleep influence information item: temperature parameter, humidity parameter, light intensity, noise, carbon dioxide concentration, inhalable particulate matter concentration, exercise law, diet rule, mental health degree, and the like. The motion law may include: statistically analyzing the type of exercise (also referred to as exercise intensity), the duration of the exercise period, the regularity of the exercise period, the law of the exercise amount, and the number of consecutive exercise days. Dietary rules include: dietary weight, multiple continuous intake, regular diet, diet, and so on. Mental health includes stress, anxiety, fatigue, grief, and depression.

Step 103: The sleep quality is evaluated according to the sleep state information and the sleep influence information, and a sleep evaluation result is obtained.

In a specific implementation, the sleep state information includes at least one sleep state information item, and the sleep influence information includes at least one sleep influence information item. corresponding,

In an implementable embodiment, the foregoing step 103 is implemented by the following method:

First, the scoring coefficient corresponding to each of the sleep state information items in the sleep state information is obtained according to a correspondence between a preset sleep state information item and a scoring coefficient.

Then, according to the correspondence between the preset sleep influence information item and the scoring coefficient, the scoring coefficient corresponding to each of the sleep influence information items in the sleep influence information is acquired.

Finally, based on all the obtained scoring coefficients, the sleep quality is evaluated and the sleep evaluation result is obtained.

In this embodiment, the correspondence between the preset sleep state information item and the scoring coefficient, and the correspondence between the preset sleep influence information item and the scoring coefficient may be pre-stored in the memory. For example, stored in a memory in the form of a table, each of the above sleep state items is in accordance with The scoring coefficient configuration policy is configured with a corresponding scoring coefficient. Each sleep state item and each sleep influence information item correspond to one scoring coefficient. The scoring coefficient can be a score, a scale, or a formula. This formula can determine a corresponding coefficient by more coefficients and calculation methods.

For details, refer to the corresponding content in the following embodiments, which are not specifically enumerated herein.

The technical solution provided by the embodiment of the present invention not only determines the sleep state information according to the acquired sleep monitoring signal, but also affects the sleep factor to be evaluated, and the evaluation parameter is more comprehensive and comprehensive, and the sleep evaluation result is more accurate.

FIG. 2 is a schematic flowchart diagram of another sleep evaluation method according to an embodiment of the present invention. The execution body of the method provided by the embodiment of the present invention may be a sleep evaluation device, which may be hardware integrated with the embedded program on the terminal, or may be an application software installed in the terminal, or may be The software and the like embedded in the terminal operating system are not limited in this embodiment of the present invention. The terminal can be any terminal device including a mobile phone, a tablet computer, a PDA (Personal Digital Assistant), a notebook computer, a desktop computer, and the like. Specifically, as shown in FIG. 2, the method provided in this embodiment includes:

Step 201: Determine sleep state information according to the acquired sleep monitoring signal.

The sleep state information includes at least one sleep state information item. For example, the sleep state information includes: a bedtime time, a wake-up time point, a sleep time point, a sleep time, a number of bed departures (from the night), a bedtime (from the night) time point, a bedtime (from the night) duration, and a wakefulness. At least one of the number of times, the awake time, the length of awake, the proportion of deep sleep, the number of body movements and turnovers, respiratory abnormalities, respiratory rate, abnormal heart rate, heart rate, arrhythmia, and sleep duration.

Step 202: Determine sleep impact information according to the obtained environmental monitoring signal, physical condition detection result, exercise record, diet record, and psychological record.

The sleep impact information includes at least one sleep influence information item. For example, the sleep influence information includes: temperature, humidity, light intensity, noise, carbon dioxide concentration, inhalable particulate matter concentration, blood oxygen saturation, blood pressure, blood sugar, exercise law, eating rule, and mental health degree. The motion law may include: statistically analyzing the type of exercise type, the duration of the exercise period, the regularity of the exercise period, the law of the exercise amount, and the number of consecutive exercise days. Dietary rules include: regularity of diet, multiple intakes, dietary time, diet, diet Wait. Mental health includes stress, anxiety, fatigue, grief, and depression.

Step 203: Acquire a scoring coefficient corresponding to each of the sleep state information items in the sleep state information according to a correspondence between a preset sleep state information item and a scoring coefficient.

In a specific implementation, the correspondence between the preset sleep state information item and the scoring coefficient may be characterized as the following tables. E.g:

Table 1 Correspondence between sleep state information items and scoring coefficients

By querying the above table 1, the scoring coefficient corresponding to each of the sleep state information items in the sleep state information can be obtained. Assuming that the bed time of the measured object is within the range of z2 to z3, the scoring coefficient is a=±a2.

It should be noted here that only some of the sleep state information items are exemplarily shown in Table 1 above, and other items may be added in practical applications, for example, the time of getting up, the time of falling asleep (the actual sleep time point), and leaving the bed. Time points, length of time to leave the bed, time to wake up, length of time to wake up, etc.

Step 204: Acquire a scoring coefficient corresponding to each of the sleep influence information items in the sleep influence information according to a correspondence between a preset sleep influence information item and a scoring coefficient.

Table 2, the correspondence between the information items of sleep environment and the scoring coefficient

Assuming that the temperature of the sleeping environment in which the subject is currently located is within the range of z2 to z3, the scoring coefficient is a'=±a2. For example, the temperature in Table 2 above has a plurality of ranges: a range of 22 ° C to 26 ° C; a range of 2 26 ° C to 30 ° C; a range of 3 30 ° C to 32 ° C; ...; each range corresponding to the scoring coefficient are: range A corresponding scoring coefficient a'=+2; a scoring coefficient corresponding to the range 2 a'=+1.5; a scoring coefficient corresponding to the range three a'=+1; Assuming that the temperature of the sleeping environment in which the subject is currently located is 26 ° C, it can be judged that 26 ° C is in the range one, and the corresponding scoring coefficient a'=+2.

Table 3 Correspondence between blood oxygen saturation and scoring system

血氧饱和度范围Oxygen saturation range	分数fraction
z1～z2Z1～z2	A＝±a1A=±a1
z2～z3Z2～z3	A＝±a2A=±a2
…...	…...

Assuming that the blood oxygen saturation of the measured body is within the range of z2 to z3, the scoring coefficient is A=±a2. For example, the blood oxygen saturation in Table 3 above has a plurality of ranges: a range of 90% to 100%; a range of 80% to 90%; ...; the corresponding scoring coefficients of each range are: a corresponding score coefficient of the range A=+2; the score coefficient corresponding to the range 2 is A=+1.5; Assuming that the blood oxygen saturation of the current arterial blood of the test subject is 94%, it can be judged that 94% is in the range one, and the corresponding scoring coefficient A=+2. It should be noted here that the blood oxygen saturation of arterial blood and venous blood is different. The above examples are for arterial blood oxygen saturation.

Table 4 Correspondence between blood pressure and scoring system

It should be noted here that the blood pressure is related to the user's weight, age, and gender, that is, the gender, age, and weight of the user's blood pressure reference range is different. Therefore, this embodiment According to these several references, a coefficient S is set, ranging from s1 to s2, s2 to s3, .... A coefficient is calculated based on body weight, age, and gender, and the corresponding scoring coefficient is found by judging the range of the coefficient corresponding to the user. Among them, the information of weight, age and gender, the user can select the corresponding item through the user interface input or through the options on the user interface.

It is assumed that the coefficient of the measured body is within the range of s2 to s3, and the blood pressure ranges from z2 to z3, and the scoring coefficient is B=±d2. For example, in the above Table 4, the blood pressure has a plurality of ranges: a range of 90 mmHg to 140 mmHg; a range of two 140 mmHg to 160 mmHg; ...; the corresponding scoring coefficients of each range are: a range corresponding to the scoring coefficient B = +2; Corresponding scoring coefficient B=+1; Assuming that the current blood pressure of the measured body is 115 mmHg, it can be judged that 115 mmHg is in the range one, and the corresponding scoring coefficient B=+2. It should be noted here that the blood pressure is divided into systolic blood pressure and diastolic blood pressure. The above cited examples are examples of systolic blood pressure; in fact, the diastolic blood pressure is also the same, and will not be exemplified here.

Table 5 Correspondence between blood glucose and scoring system

血糖范围Blood glucose range	分数fraction
z1～z2Z1～z2	C＝±c1C=±c1
z2～z3Z2～z3	C＝±c2C=±c2
…...	…...

Assuming that the blood glucose range of the test subject is monitored within the range of z2 to z3, the scoring coefficient is C=±c2. For example, the blood glucose in Table 5 above has a plurality of ranges: a range of 4.0 mmol / L to 6.0 mmol / L; a range of two 6.0 mmol / L ~ 8.0 mmol / L; ...; each range corresponding to the scoring coefficient are: range A corresponding scoring coefficient C=+2; a scoring coefficient corresponding to the range two is C=+1; Assuming that the blood glucose of the test subject is 5.5 mmol/L, it can be judged that 5.5 mmol/L is in the range one, and the corresponding scoring coefficient C=+2. What needs to be explained here is that blood sugar is divided into fasting blood sugar, one hour blood sugar after meal and two hours blood sugar after meal. The above cited examples are examples of fasting blood glucose; in fact, postprandial blood glucose is also the same, and will not be exemplified here.

Claims

A sleep evaluation method, comprising:

Determining sleep state information according to the acquired sleep monitoring signal, wherein the sleep monitoring signal is generated by monitoring a physical sign of the subject under sleep;

Determining sleep impact information according to one or more of the obtained environmental monitoring signals, physical condition detection results, exercise records, diet records, and psychological records;

Based on the sleep state information and the sleep influence information, the sleep quality is evaluated and a sleep evaluation result is obtained.
The sleep evaluation method according to claim 1, wherein the sleep state information comprises at least one sleep state information item, and the sleep influence information comprises at least one sleep influence information item;

Correspondingly, the assessing the sleep quality according to the sleep state information and the sleep influence information, and obtaining a sleep assessment result, includes:

Obtaining, according to a correspondence between the preset sleep state information item and the scoring coefficient, a scoring coefficient corresponding to each of the sleep state information items in the sleep state information;

Acquiring a scoring coefficient corresponding to each of the sleep influence information items in the sleep influence information according to a correspondence between a preset sleep influence information item and a scoring coefficient;

Evaluating sleep quality and obtaining sleep assessment results based on all of the obtained scoring coefficients;

The sleep state information item is analyzed according to a signal resolution policy corresponding to the preset state score item, and the sleep monitoring information is obtained; and the sleep influence information item is determined based on a preset impact score item.
The sleep evaluation method according to claim 2, wherein the evaluating the sleep quality and obtaining the sleep evaluation result according to all the obtained scoring coefficients comprises:

Adding all of the obtained scoring coefficients, and the obtained sum is taken as the sleep evaluation result; or

Deducting all of the scoring coefficients from the preset base score, and obtaining the difference as the sleep evaluation result; or

Obtaining weights corresponding to each of the scoring coefficients, and performing all the obtained scoring coefficients Weighted summation, resulting weighted sum as the result of the sleep assessment; or

All the obtained scoring coefficients are used as input parameters of the preset evaluation strategy, and the sleep evaluation result is obtained according to the preset evaluation strategy.
The sleep evaluation method according to claim 3, further comprising:

And obtaining, according to a correspondence between the preset score interval and the evaluation level, an evaluation level corresponding to the score interval in which the sleep evaluation result is located.
A sleep evaluation device, comprising:

a first determining module, configured to determine sleep state information according to the acquired sleep monitoring signal, wherein the sleep monitoring signal is generated by monitoring a physical sign of the measured subject in a sleep state;

a second determining module, configured to determine sleep impact information according to one or more of the obtained environmental monitoring signals, physical condition detection results, exercise records, diet records, and psychological records;

And an evaluation module, configured to evaluate sleep quality according to the sleep state information and the sleep influence information, and obtain a sleep evaluation result.
The sleep evaluation apparatus according to claim 5, wherein the sleep state information includes at least one sleep state information item, and the sleep influence information includes at least one sleep influence information item;

Correspondingly, the evaluation module comprises:

a first acquiring unit, configured to acquire a scoring coefficient corresponding to each of the sleep state information items in the sleep state information according to a correspondence between a preset sleep state information item and a scoring coefficient;

a second acquiring unit, configured to acquire a scoring coefficient corresponding to each of the sleep influence information items in the sleep influence information according to a correspondence between a preset sleep influence information item and a scoring coefficient;

a determining unit, configured to evaluate sleep quality according to all the obtained scoring coefficients and obtain a sleep evaluation result;

The sleep state information item is analyzed according to a signal resolution policy corresponding to the preset state score item, and the sleep monitoring information is obtained; and the sleep influence information item is determined based on a preset impact score item.
The sleep evaluation device according to claim 6, wherein the determining unit is specifically configured to:

Adding all of the obtained scoring coefficients, and the obtained sum is taken as the sleep evaluation result; or

Deducting all of the scoring coefficients from the preset base score, and obtaining the difference as the sleep evaluation result; or

Obtaining a weight corresponding to each of the scoring coefficients, and performing weighted summation on all the obtained scoring coefficients, and obtaining a weighted sum as the sleep evaluation result; or

All the obtained scoring coefficients are used as input parameters of the preset evaluation strategy to obtain the sleep evaluation result.
The sleep evaluation device according to claim 7, further comprising:

The obtaining module is configured to obtain an evaluation level corresponding to the score interval of the sleep evaluation result according to the correspondence between the preset score interval and the evaluation level.
A sleep evaluation system, comprising:

At least one first sensor for monitoring signs of the subject under sleep and generating a corresponding sleep monitoring signal;

At least one second sensor for monitoring a sleeping environment and generating a corresponding environmental monitoring signal, a measuring instrument for detecting physiological parameters of the measured body, and a motion monitor for monitoring and recording motion information of the measured body One or more of a recording device for recording dietary information input by the user and an evaluation device for assessing the mental health of the user;

a processor, configured to determine sleep state information according to the acquired sleep monitoring signal; determine sleep influence according to one or more of the obtained environmental monitoring signal, physical condition detection result, exercise record, diet record, and psychological record Information; evaluating sleep quality based on the sleep state information and the sleep effect information and obtaining a sleep evaluation result.
The sleep evaluation system according to claim 9, further comprising: a client device; wherein the processor is a processor built in the client device.