Method and device for evaluating sleep quality and storage medium

Abstract

The invention relates to the technical field of sleep quality evaluation, and discloses a method for evaluating sleep quality, which comprises the following steps: acquiring various sleep data of a tested user collected by sleep monitoring equipment; according to each item of sleep data of the tested user and the reference value of each item of sleep data, respectively calculating the score of each item of sleep data; calculating the total score of the sleep data according to the score of each sleep data and the weight value of each sleep data; and determining a sleep quality evaluation result of the tested user according to the total score of the sleep data. In this way, the sleep quality of the tested user can be accurately quantified in combination with the various sleep data, collected by the sleep monitoring device, of the tested user, then a more accurate sleep quality evaluation result is obtained in combination with the total score of the sleep data, and a more accurate sleep quality evaluation scheme is provided for the tested user. The invention further discloses a device for evaluating the sleep quality and a storage medium.

Description

Technical Field

[0001] The present application relates to the technical field of sleep quality evaluation, for example, to a method, device and storage medium for evaluating sleep quality. Background Art

[0002] As people's living standards continue to improve, more and more people are paying more attention to their sleep conditions, thus various sleep monitoring devices have emerged. At present, the emergence of sleep monitoring devices can monitor the sleep conditions of the users being tested, and how to reasonably use the sleep data output by sleep monitoring devices has also become the focus of users.

[0003] At present, the users can only evaluate their sleep quality simply by the sleep duration or number of awakenings output by the sleep monitoring equipment. However, the evaluation results obtained by this evaluation method are not accurate. Therefore, how to more accurately evaluate the sleep quality of the users has become a technical problem that needs to be solved urgently.

[0004] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present application, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0005] In order to provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. The summary is not an extensive review, nor is it intended to identify key / critical components or delineate the scope of protection of these embodiments, but rather serves as a prelude to the detailed description that follows.

[0006] The embodiments of the present disclosure provide a method, device, and storage medium for evaluating sleep quality, which can more accurately evaluate the sleep quality of a measured user.

[0007] In some embodiments, the method for evaluating sleep quality includes: obtaining various sleep data of the measured user collected by the sleep monitoring equipment; calculating the score of each sleep data according to the various sleep data of the measured user and the baseline value of each sleep data; calculating the total score of the sleep data according to the score of each sleep data and the weight value of each sleep data; and determining the sleep quality evaluation result of the measured user according to the total score of the sleep data.

[0008] In some embodiments, the method for evaluating sleep quality includes: Si = max(0,100-bi*(Ki-Mi) 2 ), wherein Si is the score of a certain sleep data, bi is the attenuation coefficient of the sleep data, Ki is the sleep data of the measured user, and Mi is the baseline value of the sleep data.

[0009] In some embodiments, the method for evaluating sleep quality includes: the weight values ​​of total sleep time, sleep time, light sleep percentage, deep sleep percentage, rapid eye movement percentage, awakening times, and awakening time are 0.3, 0.05, 0.1, 0.3, 0.05, 0.1, and 0.1, respectively.

[0010] In some embodiments, the method for evaluating sleep quality comprises:

[0011] S 总 =0.3*S 总时长 +0.05*S 入睡 +0.1*S 浅 +0.3*S 深 +0.05*S 快+ 0.1*S 觉次 +0.1*S 觉时

[0012] Among them, S 总 is the total score of sleep data, S 总时长 is the score of total sleep duration, S 入睡 S is the score of the duration of falling asleep, 浅 S is the score of the proportion of light sleep, 深 S is the score of deep sleep percentage, 快 S is the score of rapid eye movement ratio, 觉次 is the score of awakening times, S 觉时 Rating for awakening duration.

[0013] In some embodiments, the method for evaluating sleep quality includes: when the total score of the sleep data is lower than a first score, determining that the sleep quality evaluation result of the measured user is poor sleep quality; when the total score of the sleep data is not lower than the first score and lower than the second score, determining that the sleep quality evaluation result of the measured user is average sleep quality; when the total score of the sleep data is not lower than the second score and lower than the third score, determining that the sleep quality evaluation result of the measured user is good sleep quality; when the total score of the sleep data is not lower than the third score, determining that the sleep quality evaluation result of the measured user is excellent sleep quality.

[0014] In some embodiments, the method for evaluating sleep quality includes: obtaining the number of times the sleep monitoring device collects various sleep data of the measured user; when the number of collections meets a preset condition, determining a baseline value for each sleep data based on the various sleep data of the measured user collected multiple times by the sleep monitoring device.

[0015] In some embodiments, the method for evaluating sleep quality includes: obtaining comparison results of various sleep data with their corresponding standard data; generating sleep suggestions for the user being measured based on the comparison results; and pushing the sleep quality evaluation results and sleep suggestions to the user being measured.

[0016] In some embodiments, the device for evaluating sleep quality includes: an acquisition module, configured to obtain various sleep data of the measured user collected by the sleep monitoring equipment; a first calculation module, configured to calculate the score of each sleep data according to the various sleep data of the measured user and the baseline value of each sleep data; a second calculation module, configured to calculate the total score of the sleep data according to the score of each sleep data and the weight value of each sleep data; a determination module, configured to determine the sleep quality evaluation result of the measured user according to the total score of the sleep data.

[0017] In some embodiments, the apparatus for evaluating sleep quality includes a processor and a memory storing program instructions, and the processor is configured to execute the aforementioned method for evaluating sleep quality when running the program instructions.

[0018] In some embodiments, the storage medium stores program instructions, and when the program instructions are executed, the aforementioned method for evaluating sleep quality is executed.

[0019] The method, device and storage medium for evaluating sleep quality provided by the embodiments of the present disclosure can achieve the following technical effects: by obtaining various sleep data of the user under test collected by the sleep monitoring device; and calculating the scores of each sleep data according to the various sleep data of the user under test and the baseline values ​​of each sleep data; thereby calculating the total score of the sleep data according to the scores of each sleep data and the weight values ​​of each sleep data; and then determining the sleep quality evaluation result of the user under test according to the total score of the sleep data. In this way, the sleep quality of the user under test can be accurately quantified in combination with the various sleep data of the user under test collected by the sleep monitoring device, and then a more accurate sleep quality evaluation result can be obtained in combination with the total score of the sleep data, providing a more accurate sleep quality evaluation solution for the user under test.

[0020] The above general description and the following description are exemplary and explanatory only and are not intended to limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] One or more embodiments are exemplarily described by corresponding drawings, which do not limit the embodiments. Elements with the same reference numerals in the drawings are shown as similar elements, and the drawings do not constitute a scale limitation, and wherein:

[0022] Figure 1is a schematic diagram of a method for evaluating sleep quality provided by an embodiment of the present disclosure;

[0023] Figure 2 is a schematic diagram of a method for determining a sleep quality evaluation result provided by an embodiment of the present disclosure;

[0024] Figure 3 is a schematic diagram of a method for determining a reference value of various sleep data provided by an embodiment of the present disclosure;

[0025] Figure 4 is a schematic diagram of another method for evaluating sleep quality provided by an embodiment of the present disclosure;

[0026] Figure 5 is a schematic diagram of a device for evaluating sleep quality provided by an embodiment of the present disclosure;

[0027] Figure 6 is a schematic diagram of another device for evaluating sleep quality provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0028] In order to be able to understand the features and technical contents of the embodiments of the present disclosure in more detail, the implementation of the embodiments of the present disclosure is described in detail below in conjunction with the accompanying drawings. The attached drawings are for reference only and are not used to limit the embodiments of the present disclosure. In the following technical description, for the convenience of explanation, a full understanding of the disclosed embodiments is provided through multiple details. However, one or more embodiments can still be implemented without these details. In other cases, to simplify the drawings, well-known structures and devices can be simplified for display.

[0029] The terms "first", "second", etc. in the specification and claims of the embodiments of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchanged where appropriate, so that the embodiments of the embodiments of the present disclosure described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions.

[0030] Unless otherwise stated, the term "plurality" means two or more.

[0031] In the embodiment of the present disclosure, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B indicates: A or B.

[0032] The term "and / or" is a description of the association relationship between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or, A and B.

[0033] The term "correspondence" may refer to an association relationship or a binding relationship. The correspondence between A and B means that there is an association relationship or a binding relationship between A and B.

[0034] In the embodiments of the present disclosure, smart home appliances refer to home appliances that are formed by introducing microprocessors, sensor technology, and network communication technology into home appliances. They have the characteristics of intelligent control, intelligent perception, and intelligent application. The operation process of smart home appliances often relies on the application and processing of modern technologies such as the Internet of Things, the Internet, and electronic chips. For example, smart home appliances can be connected to electronic devices to enable users to remotely control and manage the smart home appliances.

[0035] In the embodiments of the present disclosure, the terminal device refers to an electronic device with a wireless connection function. The terminal device can communicate with the above-mentioned smart home appliances by connecting to the Internet, or can directly communicate with the above-mentioned smart home appliances through Bluetooth, WiFi, etc. In some embodiments, the terminal device is, for example, a mobile device, a computer, or a vehicle-mounted device built into a hover car, or any combination thereof. Mobile devices may include, for example, mobile phones, smart home devices, wearable devices, smart mobile devices, virtual reality devices, etc., or any combination thereof, wherein wearable devices include, for example: smart watches, smart bracelets, pedometers, etc.

[0036] Figure 1 is a schematic diagram of a method for evaluating sleep quality provided by an embodiment of the present disclosure; Figure 1 As shown, optionally, the embodiment of the present disclosure provides a method for evaluating sleep quality, comprising:

[0037] S11, the sleep monitoring device obtains various sleep data of the user being tested.

[0038] S12, the sleep monitoring device calculates scores for each sleep data item according to each sleep data item of the measured user and a baseline value of each sleep data item.

[0039] S13, the sleep monitoring device calculates the total score of the sleep data according to the scores of each sleep data and the weight values ​​of each sleep data.

[0040] S14, the sleep monitoring device determines a sleep quality evaluation result of the measured user according to the total score of the sleep data.

[0041] In this solution, the sleep monitoring device can obtain various sleep data collected by the measured user. Here, the sleep monitoring device can be a sleep monitor or a smart bracelet with sleep monitoring function. Various sleep data include total sleep time, sleep time, light sleep ratio, deep sleep ratio, rapid eye movement ratio, awakening times, and awakening time. Among them, the sleep time is also called the gradual sleep period, the light sleep ratio is the quotient of the light sleep period and the total sleep period, the deep sleep ratio is the quotient of the deep sleep period and the total sleep period, and the rapid eye movement ratio is the quotient of the rapid eye movement period and the total sleep period.

[0042] In this solution, the benchmark values ​​of various sleep data can be determined in a variety of ways. In one example, the sleep monitoring device can pre-store the benchmark values ​​of various sleep data in combination with the sleep data standards of the measured user. For example, the benchmark value of the total sleep time is 8 hours, the benchmark value of the sleep time is 0, the benchmark value of the light sleep ratio is 50%, the benchmark value of the deep sleep ratio is 18%, the benchmark value of the rapid eye movement ratio is 22%, the benchmark value of the awakening number is 0, and the benchmark value of the awakening time is 0. In another example, the benchmark values ​​of various sleep data can also be determined in the following way: the sleep monitoring device obtains the number of times it collects the various sleep data of the measured user; when the number of collections meets the preset conditions, the sleep monitoring device determines the benchmark values ​​of various sleep data according to the various sleep data of the measured user collected by the sleep monitoring device for multiple times. In this way, the benchmark values ​​of various sleep data can be accurately obtained in a variety of ways. Furthermore, after the sleep monitoring device obtains the benchmark values ​​of various sleep data, the scores of various sleep data can be calculated respectively in combination with the various sleep data of the measured user and the benchmark values ​​of various sleep data. In this way, the total sleep duration score, sleep onset duration score, light sleep percentage score, deep sleep percentage score, rapid eye movement percentage score, awakening number score, and awakening duration score can be obtained respectively.

[0043] Furthermore, the sleep monitoring device can accurately calculate the total score of the sleep data by combining the scores of each sleep data and the weight values ​​of each sleep data, so as to determine the sleep quality evaluation result of the measured user according to the total score of the sleep data after calculating the total score of the sleep data. Here, the sleep quality evaluation results include poor sleep quality, average sleep quality, good sleep quality and excellent sleep quality.

[0044] The method for evaluating sleep quality provided by the embodiment of the present disclosure is adopted, by obtaining various sleep data of the measured user collected by the sleep monitoring device; and calculating the scores of each sleep data according to the various sleep data of the measured user and the baseline values ​​of each sleep data; thereby calculating the total score of the sleep data according to the scores of each sleep data and the weight values ​​of each sleep data; and then determining the sleep quality evaluation result of the measured user according to the total score of the sleep data. In this way, the sleep quality of the measured user can be accurately quantified in combination with the various sleep data of the measured user collected by the sleep monitoring device, and then a more accurate sleep quality evaluation result can be obtained in combination with the total score of the sleep data, providing a more accurate sleep quality evaluation scheme for the measured user.

[0045] Optionally, the sleep data of the measured user includes the total sleep time, sleep time, awakening times and awakening time of the measured user, and the sleep monitoring device calculates the score of each sleep data according to the sleep data of the measured user and the baseline value of the sleep data, including:

[0046] Si=max(0,100-bi*(Ki-Mi) 2 )

[0047] Among them, Si is the score of a certain sleep data, bi is the attenuation coefficient of the sleep data, Ki is the sleep data of the measured user, and Mi is the baseline value of the sleep data.

[0048] In this solution, a certain sleep data Ki of the user being tested is the sleep data actually detected and output by the sleep monitoring device, and Mi is the reference value of the same sleep data. 总 For example, if we calculate the total sleep duration score S 总 , then the total sleep time K actually detected and output by the sleep monitoring device can be obtained 总 , the baseline value of total sleep time M 总 and the decay coefficient b of the total sleep duration 总 Then, input the above three items into S 总 =max(0,100-b 总 *(K 总 -M 总 ) 2 ) to obtain the total sleep duration score. In this way, the total sleep duration item can be accurately quantified. It can be understood that the total sleep duration score, the sleep duration score, the awakening times score, and the awakening duration score can be calculated in sequence in the above manner. In this way, accurate quantification can be performed on different items of sleep data, providing an accurate data basis for the analysis of the sleep quality of the measured user.

[0049] Optionally, the sleep data of the measured user includes the light sleep ratio, deep sleep ratio, and rapid eye movement ratio of the measured user. The sleep monitoring device calculates the score of each sleep data according to the sleep data of the measured user and the baseline value of the sleep data, including:

[0050] Si=max(0,100-bi*(100*(Ki-Mi)) 2 )

[0051] Among them, Si is the score of a certain sleep data, bi is the attenuation coefficient of the sleep data, Ki is the sleep data of the measured user, and Mi is the baseline value of the sleep data.

[0052] In this solution, a certain sleep data Ki of the user being tested is the sleep data actually detected and output by the sleep monitoring device, and Mi is the benchmark value of the same sleep data. 浅 For example, if we calculate the score S of the shallow sleep ratio 浅 , then we can obtain the light sleep ratio K of the actual detection output of the sleep monitoring device 浅 , the baseline value of light sleep percentage M 浅 And the attenuation coefficient b of the proportion of light sleep 浅 Then, input the above three items into S 浅 =max(0,100-b 浅 *(100*(K 浅 -M 浅 )) 2 ) to obtain the score of the percentage of light sleep. In this way, the percentage of light sleep can be accurately quantified. It can be understood that the above method can be used to calculate the percentage of light sleep, the percentage of deep sleep, and the percentage of rapid eye movement in sequence. In this way, it is possible to accurately quantify different items of sleep data, providing an accurate data basis for the analysis of the sleep quality of the measured user.

[0053] It should be noted that the attenuation coefficients of different items of sleep data can be pre-stored in the sleep monitoring device, and the attenuation coefficients of different items of sleep data can be obtained by R&D personnel through experiments. As an example, the attenuation coefficients of total sleep time, sleep time, light sleep percentage, deep sleep percentage, rapid eye movement percentage, awakening times, and awakening duration are 0.002, 0.044, 0.8, 0.6, 0.8, 2.5, and 0.1, respectively. In this way, the attenuation coefficients of each item of data can be obtained when calculating the score of each item of sleep data separately.

[0054] Optionally, the weight values ​​of various sleep data include:

[0055] The weight values ​​of total sleep time, sleep time, light sleep percentage, deep sleep percentage, rapid eye movement percentage, awakening times, and awakening time are 0.3, 0.05, 0.1, 0.3, 0.05, 0.1, and 0.1, respectively.

[0056] In this solution, in order to accurately calculate the total score of sleep data, the weight values ​​of various sleep data can be stored in the sleep monitoring device in advance. As a preferred solution, the weight values ​​of total sleep time, sleep time, light sleep percentage, deep sleep percentage, rapid eye movement percentage, awakening times, and awakening duration are 0.3, 0.05, 0.1, 0.3, 0.05, 0.1, and 0.1, respectively. In this way, the accurate determination of the weight values ​​of various sleep data is achieved.

[0057] Optionally, in S13, the sleep monitoring device calculates a total score of the sleep data according to the scores of each sleep data and the weight values ​​of each sleep data, including:

[0058] S 总 =0.3*S 总时长 +0.05*S 入睡 +0.1*S 浅 +0.3*S 深 +0.05*S 快+ 0.1*S 觉次 +0.1*S 觉时

[0059] Among them, S 总 is the total score of sleep data, S 总时长 is the score of total sleep duration, S 入睡 S is the score of the duration of falling asleep, 浅 S is the score of the proportion of light sleep, 深 S is the score of deep sleep percentage, 快 S is the score of rapid eye movement ratio, 觉次 is the score of awakening times, S 觉时 Rating for awakening duration.

[0060] With this solution, the total score of sleep data can be accurately calculated by combining the scores of each sleep data and the weight values ​​of each sleep data, providing an accurate data basis for the evaluation of the sleep quality of the tested user.

[0061] Figure 2 is a schematic diagram of a method for determining a sleep quality evaluation result provided by an embodiment of the present disclosure; Figure 2 As shown, optionally, in S14, the sleep monitoring device determines the sleep quality evaluation result of the measured user according to the total score of the sleep data, including:

[0062] S21, when the total score of the sleep data is lower than the first score, the sleep monitoring device determines that the sleep quality evaluation result of the measured user is poor sleep quality.

[0063] S22: When the total score of the sleep data is not lower than the first score and lower than the second score, the sleep monitoring device determines that the sleep quality evaluation result of the measured user is average.

[0064] S23, when the total score of the sleep data is not lower than the second score and lower than the third score, the sleep monitoring device determines that the sleep quality evaluation result of the measured user is good sleep quality.

[0065] S24, when the total score of the sleep data is not lower than the third score, the sleep monitoring device determines that the sleep quality evaluation result of the measured user is excellent.

[0066] In this solution, the first score, the second score and the third score can be stored in the environmental monitoring device in advance. Among them, the first score < the second score < the third score. As an example, the first score is 70 points, the second score is 80 points, and the third score is 90 points. In this way, when the total score of the sleep data is less than 70 points, the sleep monitoring device determines that the sleep quality evaluation result of the measured user is poor sleep quality. When the total score of the sleep data is not less than 70 points and less than 80 points, the sleep monitoring device determines that the sleep quality evaluation result of the measured user is general sleep quality. When the total score of the sleep data is not less than 80 points and less than 90 points, the sleep monitoring device determines that the sleep quality evaluation result of the measured user is good sleep quality. When the total score of the sleep data is not less than 90 points, the sleep monitoring device determines that the sleep quality evaluation result of the measured user is excellent sleep quality. In this way, the sleep quality evaluation result of the measured user can be accurately determined in combination with the quantitative results of the sleep data.

[0067] Figure 3 is a schematic diagram of a method for determining a reference value of various sleep data provided by an embodiment of the present disclosure; Figure 3 As shown, optionally, the baseline value of each sleep data is determined by the following method:

[0068] S31, the sleep monitoring device obtains the number of times it collects various sleep data of the measured user.

[0069] S32, when the number of collection times meets the preset condition, the sleep monitoring device determines a reference value of each sleep data according to each sleep data of the measured user collected multiple times by the sleep monitoring device.

[0070] In this solution, in order to more accurately determine the baseline value of each sleep data, the number of times the sleep monitoring device collects each sleep data of the measured user can also be obtained. And determine whether the number of collections meets the preset conditions. Specifically, if the number of collections is a multiple of N, it is determined that the number of collections meets the preset conditions. Wherein, N is 10. Further, when the number of collections meets the preset conditions, the sleep monitoring device can determine the baseline value of each sleep data according to the various sleep data of the measured user collected by the sleep monitoring device multiple times. Specifically, the sleep monitoring device determines the baseline value of each sleep data according to the various sleep data of the measured user collected by the sleep monitoring device multiple times, including: the sleep monitoring device calculates the average value of each sleep data collected multiple times, and uses the average value of each sleep data as the baseline value of each sleep data. In this way, the baseline value is determined in a more personalized way in combination with the historical sleep conditions of the measured user, so that the baseline value determined in this way is more in line with the sleep pattern of the measured user.

[0071] Figure 4 is another schematic diagram of a method for evaluating sleep quality provided by an embodiment of the present disclosure; Figure 4 As shown, optionally, the embodiment of the present disclosure provides another method for evaluating sleep quality, comprising:

[0072] S41, the sleep monitoring device obtains comparison results of various sleep data with their corresponding standard data.

[0073] S42, the sleep monitoring device generates sleep suggestions for the user being measured according to the comparison result.

[0074] S43, the sleep monitoring device pushes the sleep quality evaluation results and sleep suggestions to the user being tested.

[0075] In this solution, the sleep monitoring device obtains the comparison results of each sleep data and the corresponding standard data. Here, the standard data corresponding to each sleep data can be the standard value of each sleep data expected by the user. For example, if the user expects the sleep time to be 7 hours, the standard data of the total sleep time item is 7 hours. For example, if the sleep monitoring device obtains the total sleep time of the measured user as 6.5 hours, and the standard data of the total sleep time is 7 hours, then the comparison result is determined to be that the total sleep time of the measured user is lower than the standard value. In this way, the accurate determination of the comparison result is achieved.

[0076] Furthermore, the sleep monitoring device generates sleep suggestions for the user under test based on the comparison result, including: the sleep monitoring device obtains the generation preference and sleep suggestion content of the user under test; the sleep monitoring device generates sleep suggestions for the user under test based on the generation preference and the sleep suggestion content. The generation preference includes a generation form and a generation order. The generation form includes voice, text, pictures, etc. The generation order may be the order in which the user under test pays attention to the sleep data. For example, the order in which the user under test pays attention to the sleep data may be the number of awakenings > total sleep duration, then the generation order may be the number of awakenings, total sleep duration. The sleep monitoring device may determine the sleep suggestion corresponding to the comparison result as the sleep suggestion content. In this way, the sleep suggestion for the user under test can be accurately generated in combination with the generation preference and the sleep suggestion content.

[0077] Furthermore, the sleep monitoring device can push the sleep quality evaluation results and sleep suggestions to the tested user. In this way, the tested user can know his current sleep quality and corresponding improvement strategies through the sleep quality evaluation results and sleep suggestions, and meet the user's sleep improvement needs.

[0078] Optionally, the embodiment of the present disclosure further provides a method for pushing sleep suggestions, including:

[0079] The sleep monitoring device determines the sleep data items that affect the sleep quality based on various sleep data.

[0080] The sleep monitoring device determines sleep suggestions for improving the sleep quality of the user being measured based on the sleep data items that affect the sleep quality.

[0081] Sleep monitoring equipment pushes sleep suggestions to the users being tested.

[0082] In this embodiment, the sleep monitoring device can determine the sleep data items that affect the sleep quality based on the various sleep data. Specifically, the sleep monitoring device determines the sleep data items that affect the sleep quality based on the various sleep data, including: the sleep monitoring device obtains the baseline value of each sleep data; the sleep monitoring device calculates the deviation of each sleep data based on each sleep data and the baseline value of each sleep data. The sleep monitoring device determines the sleep data items whose deviation is not less than the preset threshold as the sleep data items that affect the sleep quality. With this solution, the sleep data items that affect the sleep quality can be accurately screened out in combination with the deviation of each sleep data.

[0083] In an optimized solution, after the sleep monitoring device obtains the deviation of each sleep data, the sleep monitoring device determines the sleep quality assessment result of the measured user according to the deviation of each sleep data. Specifically, the sleep monitoring device determines the sleep quality assessment result of the measured user according to the deviation of each sleep data, including: if the deviation of one or more sleep data is lower than the preset threshold, the sleep quality assessment result of the measured user is determined to be good sleep quality; if the deviation of one or more sleep data is between the preset threshold and the second preset threshold, the sleep quality assessment result of the measured user is determined to be general sleep quality; if the deviation of one or more sleep data is higher than the second preset threshold, the sleep quality assessment result of the measured user is determined to be poor sleep quality. The preset threshold is 10%. The second preset threshold is 20%. In this way, the sleep quality assessment result of the measured user can be accurately determined in combination with the deviation of each sleep data.

[0084] In an optimized solution, if the evaluation result indicates that the sleep quality is good and lasts for a preset time, the sleep monitoring device is controlled to record the current sleep environment data. Here, the sleep environment data includes temperature, humidity, white noise, light brightness, bed hardness, bed height, bed massage intensity and frequency, etc. As an example, the preset time can be one week. In this way, it is convenient to store and subsequently analyze the sleep data.

[0085] In an optimized solution, if the evaluation results for multiple times indicate that the sleep quality has deteriorated and the sleep quality situation lasts for a preset period of time, it is determined that the current sleep environment data is not suitable for the user being tested, and sleep suggestions need to be pushed again. In this way, the push demand of the user being tested for sleep suggestions can be accurately determined.

[0086] Optionally, the sleep monitoring device determines sleep suggestions for improving the sleep quality of the user under test based on the sleep data items that affect the sleep quality, including: the sleep monitoring device determines the target smart device and the target control strategy for improving the sleep quality of the user under test based on the sleep data items that affect the sleep quality. The sleep monitoring device determines the sleep suggestions for improving the sleep quality of the user under test as controlling the target smart device to execute the target control strategy. Here, the sleep suggestions are control suggestions for environmental devices in the user's sleep scene. In this way, the sleep suggestions can be accurately determined in combination with the sleep data items, so that the sleep suggestions determined in this way are more in line with the sleep patterns of the user under test. Furthermore, the sleep monitoring device can push sleep suggestions to the user under test.

[0087] The method for pushing sleep suggestions provided by the embodiment of the present disclosure is adopted, by obtaining various sleep data of the measured user collected by the sleep monitoring device; and determining the sleep data items that affect the sleep quality based on the various sleep data; thereby determining the sleep suggestions for improving the sleep quality of the measured user based on the sleep data items that affect the sleep quality; and then pushing the sleep suggestions to the measured user. In this way, it is possible to process and analyze the various sleep data of the measured user to determine the sleep data items that affect the sleep quality, thereby more accurately determining the sleep suggestions for improving the sleep quality of the measured user in combination with the sleep data items that affect the sleep quality, so that when pushing the sleep suggestions to the measured user, more suitable sleep suggestions can be provided to the measured user, so that the measured user can reasonably improve his sleep according to the sleep suggestions after knowing the suitable sleep suggestions, thereby effectively improving the sleep quality of the measured user.

[0088] Optionally, the sleep monitoring device determines the sleep data items that affect the sleep quality based on various sleep data, including:

[0089] The sleep monitoring device obtains the baseline value of each sleep data.

[0090] The sleep monitoring device calculates the deviation of each sleep data according to each sleep data and the reference value of each sleep data.

[0091] The sleep monitoring device determines the sleep data items whose deviation amount is not less than a preset threshold as sleep data items that affect sleep quality.

[0092] In this solution, the sleep monitoring device can obtain the benchmark values ​​of various sleep data of the tested user stored on the server. As an example, the benchmark value of the total sleep time is 8 hours, the benchmark value of the time to fall asleep is 30 minutes, the benchmark value of the proportion of light sleep is 50%, the benchmark value of the proportion of deep sleep is 18%, the benchmark value of the proportion of rapid eye movement is 22%, the benchmark value of the number of awakenings is 4, and the benchmark value of the awakening time is 30. It should be noted that the benchmark values ​​of various sleep data of different users may be the same or different, and can also be set in advance in the sleep monitoring device according to the specific situation. In this way, the accurate acquisition of the benchmark values ​​of various sleep data is achieved.

[0093] Furthermore, the sleep monitoring device calculates the deviation of each sleep data item according to each sleep data item and the reference value of each sleep data item. Here, the deviation calculation method of each sleep data item is the same. Specifically, the deviation of a sleep data item is calculated by the following algorithm:

[0094] The deviation amount of a certain sleep data = (|a certain sleep data - the reference value of this sleep data|) / the reference value of this sleep data. Specifically, taking the total sleep duration as an example. If the total sleep duration obtained by the sleep monitoring device is 6.5 hours and the reference value of the total sleep duration is 8 hours, then the deviation amount of the total sleep duration is determined to be 1.5 / 8. In this way, accurate calculation of the deviation amounts of various sleep data can be achieved.

[0095] Furthermore, the sleep monitoring device can determine the sleep data items with deviation amounts not lower than the preset threshold as the sleep data items affecting sleep quality. Among them, the preset threshold is 10%. In this way, when the calculated deviation amount is greater than 10%, it can be determined that this sleep data item deviates far from the corresponding reference value, and then it can be determined that this sleep data item is a sleep data item affecting sleep quality. In this way, accurate determination of sleep data items can be achieved.

[0096] Optionally, the sleep monitoring device determines sleep suggestions for improving the sleep quality of the measured user according to the sleep data items affecting sleep quality, including:

[0097] The sleep monitoring device determines the target intelligent device and the target control strategy for improving the sleep quality of the measured user according to the sleep data items affecting sleep quality.

[0098] The sleep monitoring device determines that the sleep suggestion for improving the sleep quality of the measured user is to control the target intelligent device to execute the target control strategy.

[0099] In this solution, the sleep monitoring device can determine the target intelligent device for improving the sleep quality of the measured user and the target control strategy for improving the sleep quality of the measured user according to the sleep data items affecting sleep quality. Furthermore, the sleep monitoring device can determine that the sleep suggestion for improving the sleep quality of the measured user is to control the target intelligent device to execute the target control strategy. For example, if the determined target intelligent device for improving the sleep quality of the measured user is an intelligent lamp and the determined target control strategy for improving the sleep quality of the measured user is to adjust the brightness of the intelligent lamp in the sleep environment where the measured user is located at the target moment, then it can be determined that the sleep suggestion for improving the sleep quality of the measured user is to control the intelligent lamp in the sleep environment where the measured user is located to adjust the brightness at the target moment. In this way, accurate determination of sleep suggestions is achieved.

[0100] Optionally, the sleep monitoring device determines the target intelligent device for improving the sleep quality of the measured user according to the sleep data items affecting sleep quality, including:

[0101] When the sleep data item is the total sleep duration, the sleep monitoring device determines the target intelligent device for improving the sleep quality of the measured user as an intelligent lamp.

[0102] When the sleep data item is the duration of falling asleep, the sleep monitoring device determines that the target smart devices for improving the sleep quality of the user being tested are the smart speakers and the smart massage devices.

[0103] When the sleep data items are the percentage of light sleep, the percentage of deep sleep or the percentage of rapid eye movement, the sleep monitoring device determines that the target smart devices for improving the sleep quality of the user being tested are the smart speakers and the smart beds.

[0104] When the sleep data item is the number of awakenings or the awakening duration, the sleep monitoring device determines that the target smart devices for improving the sleep quality of the user being tested are the smart air conditioner and the smart bed.

[0105] It can be understood that when there are fluctuations in different sleep data items, the influencing factors of the sleep environment are different. Specifically, when the sleep data item that affects sleep quality is the total sleep duration, the influencing factor of the sleep environment is determined to be the ambient light. In order to promote regular sleep for the user under test, the target smart device for improving the sleep quality of the user under test can be determined to be a smart light, so as to improve the total sleep duration of the user under test by adjusting the brightness; when the sleep data item that affects sleep quality is the duration of falling asleep, the influencing factors of the sleep environment are determined to be body comfort and / or ambient sound. In order to meet the sleeping conditions of the user under test, the target smart device for improving the sleep quality of the user under test can be determined to be a smart speaker and a smart massage device, so as to improve the duration of falling asleep of the user under test by improving body comfort and adjusting ambient sound; when the sleep data item that affects sleep quality is light In the case of the percentage of light sleep, deep sleep or rapid eye movement, the factors affecting the sleeping environment are determined to be the softness and hardness of the bed and the ambient sound. In order to relax the stress and enter a comfortable sleep after the user falls asleep, the target smart device for improving the sleep quality of the tested user can be determined to be a smart speaker and a smart bed, so as to improve the percentage of light sleep, deep sleep or rapid eye movement of the tested user by adjusting the softness and hardness of the bed and the ambient sound; in the case that the sleep data item affecting the sleep quality is the number of awakenings or the duration of awakening, the factors affecting the sleeping environment are determined to be the ambient temperature and humidity and body comfort. The target smart device for improving the sleep quality of the tested user can be determined to be a smart air conditioner and a smart bed, so as to improve the number of awakenings or the duration of awakening of the tested user by adjusting the pressure mode of the smart bed and the ambient temperature and humidity. With this solution, the target smart device can be accurately determined in combination with the sleep data items that affect the sleep quality.

[0106] Optionally, the sleep monitoring device determines a target control strategy for improving the sleep quality of the user being measured according to the sleep data items that affect the sleep quality, including:

[0107] When the sleep data item is the total sleep duration, the sleep monitoring device determines that the target control strategy for improving the sleep quality of the measured user is to adjust the brightness of the smart light in the sleeping environment of the measured user at the target time.

[0108] When the sleep data item is the duration of falling asleep, the sleep monitoring device determines that the target control strategy for improving the sleep quality of the user being tested is to start the smart massage device according to the preset intensity and preset duration while controlling the smart speaker to play white noise.

[0109] When the sleep data item is the percentage of light sleep, deep sleep or rapid eye movement, the sleep monitoring device determines that the target control strategy for improving the sleep quality of the user being tested is to adjust the softness and hardness of the smart bed while controlling the smart speaker to play white noise.

[0110] When the sleep data item is the number of awakenings or the duration of awakening, the sleep monitoring device determines that the target control strategy for improving the sleep quality of the user being tested is to control the smart air conditioner to operate in dehumidification mode at the target set temperature while controlling the smart bed to start zero pressure mode.

[0111] In this solution, when the sleep data item is the total sleep duration, the sleep monitoring device determines that the target control strategy for improving the sleep quality of the measured user is to adjust the brightness of the smart light in the sleeping environment of the measured user at the target time. Among them, the target time can be determined by the average of the work and rest rules of the measured user. In this way, the total sleep duration of the measured user is improved by brightness adjustment. In the case where the sleep data item is the duration of falling asleep, the sleep monitoring device determines that the target control strategy for improving the sleep quality of the measured user is to start the smart massage device according to the preset intensity and preset duration while controlling the smart speaker to play white noise. Here, the preset intensity and preset duration can be determined by the massage habits of the measured user. In this way, the duration of falling asleep of the measured user is improved by improving body comfort and environmental sound adjustment. In the case where the sleep data item is the proportion of light sleep, the proportion of deep sleep or the proportion of rapid eye movement, the sleep monitoring device determines that the target control strategy for improving the sleep quality of the measured user is to adjust the softness and hardness of the smart bed while controlling the smart speaker to play white noise. Here, the softness and hardness of the smart bed can be adjusted according to the comfort habits of the measured user. In this way, the proportion of light sleep, deep sleep or rapid eye movement of the user being tested is improved by adjusting the softness and hardness of the bed and the ambient sound. When the sleep data item is the number of awakenings or the duration of awakenings, the sleep monitoring device determines that the target control strategy for improving the sleep quality of the user being tested is to control the smart air conditioner to run the dehumidification mode at the target setting temperature while controlling the smart bed to start the zero pressure mode. The target setting temperature is the comfortable sleeping temperature for the user being tested. As an example, the target setting temperature can be 26°C. In this way, the number of awakenings or the duration of awakening of the user being tested is improved by adjusting the pressure mode of the smart bed and the ambient temperature and humidity.

[0112] In an optimized solution, if the smart monitoring device detects that the user being tested is snoring, the sleep recommendation is determined to control the smart bed or smart pillow to start the anti-snoring mode, and the sleep recommendation is pushed to the user being tested, effectively improving the user's snoring during sleep.

[0113] Optionally, the sleep monitoring device pushes sleep suggestions to the user being tested, including:

[0114] When there are multiple sleep data items, the sleep monitoring device determines a target sleep data item with the highest priority.

[0115] The sleep monitoring device preferentially pushes target sleep recommendations determined by the target sleep data items to the user being tested.

[0116] In this solution, if it is determined that there are multiple sleep data items that affect sleep quality, the target sleep data item with the highest priority can be determined, so that the sleep monitoring device can give priority to pushing the target sleep suggestion determined by the target sleep data item to the user being tested. In this way, the user being tested can quickly learn the target sleep suggestion determined by the target sleep data item with the highest priority, so that the user being tested can improve the target sleep data item in time according to the target sleep suggestion, thereby meeting the user being tested's demand for improving sleep quality.

[0117] Optionally, the sleep monitoring device determines the target sleep data item with the highest priority, including:

[0118] The sleep monitoring device obtains the baseline value of each sleep data.

[0119] The sleep monitoring device calculates the deviation of each sleep data according to each sleep data and the reference value of each sleep data.

[0120] The sleep monitoring device determines the sleep data item with the highest deviation as the target sleep data item with the highest priority.

[0121] In this solution, the baseline values ​​of each sleep data item can be obtained in turn and the deviation of each sleep data item can be calculated in the above manner. Furthermore, the sleep monitoring device compares the deviations of each sleep data item and determines the sleep data item with the highest deviation as the target sleep data item with the highest priority. In this way, the target sleep data item can be accurately determined by accurately combining the comparison results of the deviations of each sleep data item.

[0122] Optionally, after the sleep monitoring device pushes sleep suggestions to the user being tested, the method further includes:

[0123] When receiving feedback from the tested user indicating that the user accepts the sleep suggestion, adjusting the device according to the pushed suggestion;

[0124] When receiving feedback information from the tested user indicating that the user does not accept the sleep suggestion, the control scheme of each device in the current sleep environment is used as the best sleep suggestion and stored in the server.

[0125] With this solution, various devices in the current sleeping environment can be adaptively adjusted according to the feedback of the tested user to meet the environmental equipment adjustment needs of the tested user.

[0126] In an optimized solution, if the feedback information of the user under test indicates that he does not accept the sleep advice, and the sleep monitoring device continues to receive the feedback information for a preset number of times, the sleep advice push to the user under test will stop. The preset number of times can be three times. With this solution, it is avoided that the sleep advice is still pushed to the user under test when the user under test does not need to receive the sleep advice, thus saving power resources.

[0127] Figure 5 is a schematic diagram of a device for evaluating sleep quality provided by an embodiment of the present disclosure; Figure 5 As shown, the embodiment of the present disclosure provides a device for evaluating sleep quality, including an acquisition module 51, a first calculation module 52, a second calculation module 53 and a determination module 54. The acquisition module 51 is configured to obtain various sleep data of the measured user collected by the sleep monitoring device; the first calculation module 52 is configured to calculate the score of each sleep data according to the various sleep data of the measured user and the reference value of each sleep data; the second calculation module 53 is configured to calculate the total score of the sleep data according to the score of each sleep data and the weight value of each sleep data; the determination module 54 is configured to determine the sleep quality evaluation result of the measured user according to the total score of the sleep data.

[0128] The device for evaluating sleep quality provided by the embodiment of the present disclosure is used to obtain various sleep data of the user under test collected by the sleep monitoring device; and the scores of various sleep data are calculated respectively according to the various sleep data of the user under test and the baseline values ​​of various sleep data; thus, the total score of the sleep data is calculated according to the scores of various sleep data and the weight values ​​of various sleep data; and then the sleep quality evaluation result of the user under test is determined according to the total score of the sleep data. In this way, the sleep quality of the user under test can be accurately quantified in combination with the various sleep data of the user under test collected by the sleep monitoring device, and then a more accurate sleep quality evaluation result can be obtained in combination with the total score of the sleep data, so as to provide a more accurate sleep quality evaluation scheme for the user under test.

[0129] Figure 6 is another schematic diagram of a device for evaluating sleep quality provided by an embodiment of the present disclosure; Figure 6 As shown, an embodiment of the present disclosure provides a device for evaluating sleep quality, including a processor 100 and a memory 101. Optionally, the device may also include a communication interface 102 and a bus 103. The processor 100, the communication interface 102, and the memory 101 may communicate with each other through the bus 103. The communication interface 102 may be used for information transmission. The processor 100 may call the logic instructions in the memory 101 to execute the method for evaluating sleep quality of the above embodiment.

[0130] In addition, the logic instructions in the memory 101 described above may be implemented in the form of software functional units and when sold or used as independent products, may be stored in a computer-readable storage medium.

[0131] The memory 101 is a computer-readable storage medium that can be used to store software programs and computer executable programs, such as program instructions / modules corresponding to the method in the embodiment of the present disclosure. The processor 100 executes the function application and data processing by running the program instructions / modules stored in the memory 101, that is, the method for evaluating sleep quality in the above embodiment is implemented.

[0132] The memory 101 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application required for at least one function; the data storage area may store data created according to the use of the terminal device, etc. In addition, the memory 101 may include a high-speed random access memory and may also include a non-volatile memory.

[0133] An embodiment of the present disclosure provides a sleep monitoring device, comprising the above-mentioned apparatus for evaluating sleep quality.

[0134] An embodiment of the present disclosure provides a computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are configured to execute the above-mentioned method for evaluating sleep quality.

[0135] An embodiment of the present disclosure provides a computer program product, which includes a computer program stored on a computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer executes the above-mentioned method for evaluating sleep quality.

[0136] The computer-readable storage medium mentioned above may be a transient computer-readable storage medium or a non-transitory computer-readable storage medium.

[0137] The technical solution of the embodiment of the present disclosure can be embodied in the form of a software product, which is stored in a storage medium and includes one or more instructions for enabling a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in the embodiment of the present disclosure. The aforementioned storage medium may be a non-transient storage medium, including: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes, or a transient storage medium.

[0138] The above description and the accompanying drawings fully illustrate the embodiments of the present disclosure so that those skilled in the art can practice them. Other embodiments may include structural, logical, electrical, process and other changes. The embodiments represent only possible changes. Unless explicitly required, separate components and functions are optional, and the order of operation may vary. The parts and features of some embodiments may be included in or replace the parts and features of other embodiments. Moreover, the words used in this application are only used to describe the embodiments and are not used to limit the claims. As used in the description of the embodiments and the claims, unless the context clearly indicates, the singular forms of "a", "an" and "the" are intended to include plural forms as well. Similarly, the term "and / or" as used in this application refers to any and all possible combinations of listings containing one or more associated ones. In addition, when used in the present application, the term "comprise" and its variants "comprises" and / or comprising refer to the presence of stated features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or groups thereof. In the absence of further restrictions, the elements defined by the sentence "comprising a ..." do not exclude the presence of other identical elements in the process, method or device comprising the elements. In this article, each embodiment may focus on the differences from other embodiments, and the same and similar parts between the various embodiments may refer to each other. For the methods, products, etc. disclosed in the embodiments, if they correspond to the method part disclosed in the embodiments, then the relevant parts can refer to the description of the method part.

[0139] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software may depend on the specific application and design constraints of the technical solution. The technicians may use different methods for each specific application to implement the described functions, but such implementations should not be considered to exceed the scope of the embodiments of the present disclosure. The technicians may clearly understand that, for the convenience and simplicity of description, the specific working processes of the systems, devices and units described above may refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here.

[0140] In the embodiments disclosed herein, the disclosed methods and products (including but not limited to devices, equipment, etc.) can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units can be only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between each other shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms. The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to implement this embodiment. In addition, each functional unit in the embodiment of the present disclosure may be integrated in a processing unit, or each unit may exist physically alone, or two or more units may be integrated in one unit.

[0141] The flowchart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to the embodiment of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. In some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. In the description corresponding to the flowchart and the block diagram in the accompanying drawings, the operations or steps corresponding to different boxes can also occur in a different order from the order disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based system that performs the specified functions or actions, or may be implemented by a combination of dedicated hardware and computer instructions.

Claims

1. A method for evaluating sleep quality, characterized in that: include: Obtain various sleep data of the tested user collected by the sleep monitoring device; Calculate scores for each sleep data item according to each sleep data item of the measured user and the baseline value of each sleep data item; Calculate the total score of the sleep data according to the scores of the various sleep data and the weight values ​​of the various sleep data; A sleep quality evaluation result of the measured user is determined according to the total score of the sleep data.

2. The method according to claim 1, characterized in that The sleep data of the measured user includes the total sleep time, sleep time, awakening times and awakening time of the measured user. The sleep data score is calculated based on the sleep data of the measured user and the reference value of the sleep data, including: Si=max(0.100-bi*(Ki-Mi) 2 ) Among them, Si is the score of a certain sleep data, bi is the attenuation coefficient of the sleep data, Ki is the sleep data of the measured user, and Mi is the baseline value of the sleep data.

3. The method according to claim 1, characterized in that The sleep data include total sleep time, sleep duration, light sleep ratio, deep sleep ratio, rapid eye movement ratio, awakening times, and awakening duration. The weight values ​​of the sleep data include: The weight values ​​of the total sleep duration, the sleep duration, the light sleep percentage, the deep sleep percentage, the rapid eye movement percentage, the number of awakenings, and the awakening duration are 0.3, 0.05, 0.1, 0.3, 0.05, 0.1, and 0.1, respectively.

4. The method according to claim 3, characterized in that The total score of the sleep data is calculated according to the scores of the various sleep data and the weight values ​​of the various sleep data, including: S 总 =0.3*S 总时长 +0.05*S 入睡 +0.1*S 浅 +0.3*S 深 +0.05*S 快+ 0.1*S 觉次 +0.1*S 觉时 Among them, S 总 is the total score of sleep data, S 总时长 is the score of total sleep duration, S 入睡 S is the score of the duration of falling asleep, 浅 S is the score of the proportion of light sleep, 深 S is the score of deep sleep percentage, 快 S is the score of rapid eye movement ratio, 觉次 is the score of awakening times, S 觉时 Rating for awakening duration.

5. The method according to claim 1, characterized in that Determining the sleep quality evaluation result of the measured user according to the total score of the sleep data includes: When the total score of the sleep data is lower than the first score, determining that the sleep quality evaluation result of the measured user is poor sleep quality; When the total score of the sleep data is not lower than the first score and lower than the second score, determining that the sleep quality evaluation result of the measured user is average sleep quality; When the total score of the sleep data is not lower than the second score and lower than the third score, determining that the sleep quality evaluation result of the measured user is good in sleep quality; When the total score of the sleep data is not lower than the third score, it is determined that the sleep quality evaluation result of the measured user is excellent.

6. The method according to any one of claims 1 to 5, characterized in that: The baseline values ​​for each sleep data are determined in the following ways: Obtaining the number of times the sleep monitoring device collects various sleep data of the measured user; When the number of collection times meets a preset condition, a reference value of each sleep data is determined according to each sleep data of the measured user collected multiple times by the sleep monitoring device.

7. The method according to claim 1, characterized in that After determining the sleep quality evaluation result of the measured user, the method further includes: Obtain comparison results of various sleep data with their corresponding standard data; Generating a sleep suggestion for the measured user according to the comparison result; The sleep quality evaluation result and the sleep suggestion are pushed to the measured user.

8. A device for evaluating sleep quality, characterized in that: include: An acquisition module is configured to obtain various sleep data of the user being tested collected by the sleep monitoring device; A first calculation module is configured to calculate scores for each sleep data item according to each sleep data item of the measured user and a reference value of each sleep data item; A second calculation module is configured to calculate a total score of the sleep data according to the scores of the various sleep data and the weight values ​​of the various sleep data; The determination module is configured to determine the sleep quality evaluation result of the measured user according to the total score of the sleep data.

9. A device for evaluating sleep quality, comprising a processor and a memory storing program instructions, characterized in that: The processor is configured to execute the method for evaluating sleep quality according to any one of claims 1 to 7 when running the program instructions.

10. A storage medium storing program instructions, characterized in that: When the program instructions are executed, the method for evaluating sleep quality according to any one of claims 1 to 7 is executed.

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