A human sleep data analysis method based on intelligent mattress monitoring

Abstract

The present invention relates to the technical field of human sleep data analysis, and specifically discloses a human sleep data analysis method based on intelligent mattress monitoring, the method comprising: collecting sleeping state information, analyzing sleeping difficulty, analyzing sleeping environment comfort, confirming user sleep stages, analyzing sleep process quality and comprehensive sleep quality analysis; the present invention comprehensively analyzes whether a target user has sleep disorder by combining whether the target user has sleeping difficulty and whether the target user has sleep quality problems during sleep, thereby improving the comprehensiveness and accuracy of the target user's sleep problem assessment, providing the target user with personalized sleep advice, reducing the impact on the target user's physical and mental health, improving the timeliness of the discovery and treatment of sleeping difficulty, and for users with sleep disorders, helping doctors or therapists to formulate more effective treatment plans.

Description

Technical Field

[0001] The present invention relates to the technical field of human sleep data analysis, and in particular to a human sleep data analysis method based on intelligent mattress monitoring. Background Art

[0002] As people's pace of life accelerates, sleep quality has become an important factor affecting people's health. Traditional sleep monitoring methods, such as polysomnography, can provide detailed sleep data, but the equipment is complex, the operation is cumbersome, and it needs to be performed in a specific environment, which limits its popularity and application. In recent years, smart mattresses, as a new type of sleep monitoring tool, have gradually attracted people's attention with their convenience, comfort, and strong real-time performance. However, most of the smart mattresses on the market currently only have basic sleep monitoring functions, and the analysis and processing of data are relatively simple. Therefore, in order to evaluate the user's sleep quality, it is necessary to analyze and process the user's human sleep data.

[0003] There are still the following problems in the existing methods for analyzing and processing users' human sleep data: 1. Currently, only the sleep quality of the user during sleep is analyzed, and whether the user has difficulty falling asleep is not combined to comprehensively analyze whether the user has sleep disorders, resulting in an incomplete and inaccurate assessment of the user's sleep problems. Long-term neglect of difficulty falling asleep may lead to more serious sleep problems, which in turn affects the user's physical and mental health, and reduces the timeliness of the discovery and treatment of difficulty falling asleep.

[0004] 2. Currently, when analyzing the sleep quality of users during sleep, the comfort of the sleeping environment is not analyzed in combination with the indoor sleeping environment information, thereby failing to correct the impact of the comfort of the sleeping environment on the sleep quality during sleep, reducing the accuracy of the sleep quality analysis during sleep, and ignoring the interference of environmental factors, resulting in the user's sleep problems not being effectively solved, and failing to identify and improve the bad sleeping environment in a timely manner, thereby reducing the user's sleep quality.

[0005] 3. Currently, when analyzing the sleep quality of users during sleep, the sleep stage of the target user is not confirmed in combination with the sleep status information of the target user. If the sleep stage of the user is not understood, it is impossible to provide the user with personalized sleep suggestions. For users with sleep disorders, it is impossible to help doctors or therapists develop more effective treatment plans. At the same time, it is impossible to comprehensively evaluate the health status of their sleep cycle, and thus it is impossible to provide effective intervention measures. Summary of the invention

[0006] In view of this, in order to solve the problems raised in the above background technology, a human sleep data analysis method based on smart mattress monitoring is proposed.

[0007] The purpose of the present invention can be achieved through the following technical solutions: The present invention provides a human sleep data analysis method based on smart mattress monitoring, comprising the following steps: S1, sleeping state information collection: extracting the time points corresponding to the target user's preparation for falling asleep on each sleep monitoring day, and collecting the heart rate and respiratory rate corresponding to each monitoring time point within a period of time after the target user is ready to fall asleep on each sleep monitoring day.

[0008] S2. Analysis of difficulty falling asleep: Analyze the difficulty falling asleep of the target users, and compare and analyze whether the target users have difficulty falling asleep, and provide feedback.

[0009] S3. Sleeping environment comfort analysis: Collect the sleeping environment information corresponding to each monitoring time period after the target user has entered the sleeping state on each sleep monitoring day, and analyze the sleeping environment comfort corresponding to each monitoring time period on each sleep monitoring day.

[0010] S4. Confirmation of user sleep stage: Collect the target user's turning over times in each monitoring time period on each sleep monitoring day, as well as the breathing rate and heart rate at each sampling point, to confirm the target user's sleep stage corresponding to each monitoring time period on each sleep monitoring day, where the sleep stage includes deep sleep and light sleep.

[0011] S5. Sleep quality analysis: Analyze the target user's sleep quality index during sleep, and compare and analyze whether the target user has sleep quality problems during sleep, and provide feedback.

[0012] S6. Comprehensive sleep quality analysis: Analyze the comprehensive sleep quality index of the target user, and compare and analyze whether the target user has sleep disorders, and provide feedback.

[0013] Specifically, according to the target user's difficulty in falling asleep, a target user's difficulty in falling asleep index is constructed and analyzed, and the specific construction process is: A1. According to the heart rate and breathing rate corresponding to each monitoring time point within a period of time after the target user is ready to fall asleep on each sleep monitoring day, the time point corresponding to the target user entering the sleep state on each sleep monitoring day is confirmed.

[0014] A2. Compare the time point when the target user enters the sleep state on each sleep monitoring day with the time point when the target user is ready to fall asleep, and obtain the target user's sleep duration on each sleep monitoring day, recorded as ,in, Indicates the number of the sleep monitoring day, .

[0015] A3. Calculate the target user's difficulty falling asleep index , ,in, and They represent the reference sleep duration and sleep duration deviation respectively. Indicates the number of sleep monitoring days. Represents a natural constant.

[0016] Specifically, the specific process of confirming the time point corresponding to the target user entering the sleep state on each sleep monitoring day is as follows: B1, recording the heart rate and respiratory rate corresponding to each monitoring time point within a period of time after the target user is ready to fall asleep on each sleep monitoring day as and ,in, Indicates the number of the monitoring time point, .

[0017] B2. Extract the corresponding reference heart rate and respiratory rate when entering the sleep state from the database and record them as and .

[0018] B3. Calculate the sleep stability of the target user at each monitoring time point within a period of time after the target user prepares to fall asleep on each sleep monitoring day. , ,in, and They represent the heart rate deviation and respiratory rate deviation of the set reference respectively. and They represent the weights of the set heart rate deviation and breathing frequency deviation corresponding to the sleep state stability assessment. .

[0019] B4. Compare the sleep state smoothness corresponding to each monitoring time point within a period of time after the target user prepares to fall asleep on each sleep monitoring day with the sleep state smoothness of the set reference, and record the first monitoring time point corresponding to the time when the sleep state smoothness of the target user within a period of time after the target user prepares to fall asleep on each sleep monitoring day is greater than the sleep state smoothness of the set reference as the time point corresponding to entering the sleep state.

[0020] Specifically, the sleeping environment information includes indoor temperature, indoor humidity and indoor light intensity.

[0021] Specifically, the specific process of analyzing the target user's sleeping environment comfort corresponding to each monitoring time period on each sleep monitoring day is as follows: C1, extracting the indoor temperature, indoor humidity and indoor light intensity from the sleeping environment information corresponding to each monitoring time period after the target user has entered the sleeping state on each sleep monitoring day, and recording them as , and ,in, Indicates the number of the monitoring time period. .

[0022] C2. Extract the appropriate indoor temperature, appropriate indoor humidity and appropriate indoor light intensity in the sleeping state from the database and record them as , and .

[0023] C3. Calculate the temperature suitability index, humidity suitability index and light suitability index of the target user in each monitoring period of each sleep monitoring day, and record them as , and .

[0024] C4. Calculate the target user's sleeping environment comfort level for each monitoring period on each sleep monitoring day , ,in, , and They represent the weights of the set temperature suitability index, humidity suitability index, and light suitability index corresponding to the comfort level of the sleeping environment. .

[0025] Specifically, the calculation formula of the temperature suitability index corresponding to each monitoring time period of the target user on each sleep monitoring day is: ,in, Indicates the appropriate indoor temperature deviation from the set reference.

[0026] Specifically, the specific process of confirming the sleep stage corresponding to each monitoring time period of each sleep monitoring day of the target user is as follows: D1. Based on the number of turning over of the target user in each monitoring time period of each sleep monitoring day and the breathing frequency and heart rate of each sampling point, the sleep quality index of the target user in each monitoring time period of each sleep monitoring day is calculated. .

[0027] D2. Compare the target user's sleep quality index in each monitoring time period on each sleep monitoring day with the set reference sleep quality index, and record the monitoring time period when the sleep quality index is greater than or equal to the set reference sleep quality index as a deep sleep stage, otherwise, it is recorded as a light sleep stage, and count the number of deep sleep stages of the target user on each sleep monitoring day.

[0028] Specifically, the specific process of calculating the sleep quality index of the target user in each monitoring time period of each sleep monitoring day is as follows: E1. Record the number of turning over of the target user in each monitoring time period of each sleep monitoring day as .

[0029] E2. Using the sampling point as the horizontal coordinate and the breathing frequency as the vertical coordinate, a breathing frequency change curve of the target user in each monitoring time period of each sleep monitoring day is constructed, and the slope value is located from the curve as the breathing frequency change rate of the target user in each monitoring time period of each sleep monitoring day, which is marked as .

[0030] E3. Calculate the target user's breathing rate change during each monitoring period on each sleep monitoring day , ,in, Indicates the respiratory rate change rate of the set reference.

[0031] E4. Similarly, calculate the heart rate variation of the target user in each monitoring period on each sleep monitoring day .

[0032] E5. Calculate the target user's sleep quality index for each monitoring period on each sleep monitoring day , ,in, , and They represent the weights of sleep quality assessment corresponding to the set number of turning over, breathing rate change and heart rate change. , , and They respectively represent the set reference number of turning over, the comfort of the sleeping environment and the sleep quality compensated for the unit deviation of the sleeping environment comfort.

[0033] Specifically, the calculation formula of the sleep quality index of the target user during sleep is: ,in, Indicates the target user's sleep quality index during sleep. Indicates the number of deep sleep stages of the target user on each sleep monitoring day. Indicates the number of monitoring time periods. Indicates the number of sleep monitoring days. Indicates the percentage of deep sleep stage for setting reference.

[0034] Specifically, the calculation formula of the comprehensive sleep quality index of the target user is: ,in, Represents the comprehensive sleep quality index of the target user, and They represent the weights of the set difficulty falling asleep index and the sleep quality index during sleep corresponding to the comprehensive sleep quality assessment. .

[0035] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention comprehensively analyzes whether the target user has sleep disorders by combining whether the target user has difficulty falling asleep and whether the target user has sleep quality problems during sleep, thereby improving the comprehensiveness and accuracy of the target user's sleep problem assessment, reducing the impact on the target user's physical and mental health, and improving the timeliness of the discovery and treatment of difficulty falling asleep.

[0036] (2) The present invention analyzes the target user's sleeping environment comfort level corresponding to each monitoring time period on each sleep monitoring day by combining indoor temperature, indoor humidity and indoor light intensity, thereby correcting the impact on sleep quality during the sleep process, thereby improving the accuracy of sleep quality analysis during the sleep process, effectively solving the target user's sleep problems, and timely identifying and improving a bad sleeping environment, thereby improving the user's sleep quality.

[0037] (3) The present invention combines the number of times the target user turns over in each monitoring time period on each sleep monitoring day as well as the respiratory rate and heart rate at each sampling point to confirm the sleep stage corresponding to each monitoring time period on each sleep monitoring day, and can provide personalized sleep suggestions for the target user. For users with sleep disorders, it can help doctors or therapists develop more effective treatment plans, and comprehensively evaluate the health status of their sleep cycle, so as to provide effective intervention measures. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0039] Figure 1 The figure is a schematic flow chart of the steps of the method of the present invention. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] See also Figure 1As shown, the present invention provides a human sleep data analysis method based on smart mattress monitoring, including: S1, sleeping state information collection: extracting the time points corresponding to when the target user is preparing to fall asleep on each sleep monitoring day, and collecting the heart rate and respiratory rate corresponding to each monitoring time point within a period of time after the target user is preparing to fall asleep on each sleep monitoring day.

[0042] It should be noted that the method for confirming the time point corresponding to the target user's preparation for falling asleep on each sleep monitoring day is: video capture of the target user's face on each sleep monitoring day is performed, the captured video is divided into pictures in frames, and the time point corresponding to each picture is obtained, and the pupil area of ​​the target user in each picture is scanned by a pupil scanner installed indoors. When the pupil area is 0, it indicates that the target user is in a completely closed-eye state. When the pupil area is consistent with the pupil area in a resting state, it indicates that the target user is in a fully open-eye state. Pictures of the target user in a completely closed-eye state are extracted, and the time point corresponding to the first picture in the completely closed-eye state is used as the corresponding time point when preparing to fall asleep.

[0043] It should also be noted that the heart rate and breathing rate corresponding to each monitoring time point of the target user within a period of time after preparing to fall asleep on each sleep monitoring day are extracted from the monitoring data of the target smart mattress.

[0044] S2. Analysis of difficulty falling asleep: Analyze the difficulty falling asleep of the target users, and compare and analyze whether the target users have difficulty falling asleep, and provide feedback.

[0045] In a specific embodiment of the present invention, the target user's difficulty in falling asleep is constructed and analyzed according to the target user's difficulty in falling asleep. The specific construction process is: A1. According to the heart rate and breathing rate corresponding to each monitoring time point within a period of time after the target user prepares to fall asleep on each sleep monitoring day, the time point corresponding to the target user entering the sleep state on each sleep monitoring day is confirmed.

[0046] In a specific embodiment of the present invention, the specific process of confirming the time point corresponding to the target user entering the sleep state on each sleep monitoring day is as follows: B1, the heart rate and respiratory rate corresponding to each monitoring time point within a period of time after the target user is ready to fall asleep on each sleep monitoring day are recorded as and ,in, Indicates the number of the monitoring time point, .

[0047] B2. Extract the corresponding reference heart rate and respiratory rate when entering the sleep state from the database and record them as and .

[0048] B3. Calculate the sleep stability of the target user at each monitoring time point within a period of time after the target user prepares to fall asleep on each sleep monitoring day. , ,in, and They represent the heart rate deviation and respiratory rate deviation of the set reference respectively. and They represent the weights of the set heart rate deviation and breathing frequency deviation corresponding to the sleep state stability assessment. .

[0049] In a specific embodiment of the present invention, The setting value of is 0.5. The setting value is 0.5.

[0050] B4. Compare the sleep state smoothness corresponding to each monitoring time point within a period of time after the target user prepares to fall asleep on each sleep monitoring day with the sleep state smoothness of the set reference, and record the first monitoring time point corresponding to the time when the sleep state smoothness of the target user within a period of time after the target user prepares to fall asleep on each sleep monitoring day is greater than the sleep state smoothness of the set reference as the time point corresponding to entering the sleep state.

[0051] A2. Compare the time point when the target user enters the sleep state on each sleep monitoring day with the time point when the target user is ready to fall asleep, and obtain the target user's sleep duration on each sleep monitoring day, recorded as ,in, Indicates the number of the sleep monitoring day, .

[0052] A3. Calculate the target user's difficulty falling asleep index , ,in, and They represent the reference sleep duration and sleep duration deviation respectively. Indicates the number of sleep monitoring days. Represents a natural constant.

[0053] It should be noted that the process of analyzing whether the target user has difficulty falling asleep is: comparing the target user's difficulty falling asleep index with the set reference difficulty falling asleep index. If the target user's difficulty falling asleep index is greater than or equal to the set reference difficulty falling asleep index, it indicates that the target user has difficulty falling asleep.

[0054] S3. Sleeping environment comfort analysis: Collect the sleeping environment information corresponding to each monitoring time period after the target user has entered the sleeping state on each sleep monitoring day, and analyze the sleeping environment comfort corresponding to each monitoring time period on each sleep monitoring day.

[0055] In a specific embodiment of the present invention, the sleeping environment information includes indoor temperature, indoor humidity and indoor light intensity.

[0056] It should be noted that the indoor temperature, indoor humidity and indoor light intensity are respectively collected by a temperature sensor, a humidity sensor and a light intensity sensor installed indoors.

[0057] In a specific embodiment of the present invention, the specific process of analyzing the sleep environment comfort of the target user corresponding to each monitoring time period on each sleep monitoring day is as follows: C1, extracting the indoor temperature, indoor humidity and indoor light intensity from the sleep environment information corresponding to each monitoring time period after the target user has entered the sleep state on each sleep monitoring day, and recording them as , and ,in, Indicates the number of the monitoring time period. .

[0058] C2. Extract the appropriate indoor temperature, appropriate indoor humidity and appropriate indoor light intensity in the sleeping state from the database and record them as , and .

[0059] C3. Calculate the temperature suitability index, humidity suitability index and light suitability index of the target user in each monitoring period of each sleep monitoring day, and record them as , and .

[0060] In a specific embodiment of the present invention, the calculation formula of the temperature suitability index corresponding to each monitoring time period of the target user on each sleep monitoring day is: ,in, Indicates the appropriate indoor temperature deviation from the set reference.

[0061] It should be noted that the calculation formula for the humidity suitability index corresponding to each monitoring time period of the target user on each sleep monitoring day is: ,in, Indicates the indoor humidity deviation from the set reference.

[0062] It should be noted that the calculation formula for the light suitability index corresponding to each monitoring time period of the target user on each sleep monitoring day is: ,in, Indicates the indoor light intensity deviation from the set reference.

[0063] C4. Calculate the target user's sleeping environment comfort level for each monitoring period on each sleep monitoring day , ,in, , and They represent the weights of the set temperature suitability index, humidity suitability index, and light suitability index corresponding to the comfort level of the sleeping environment. .

[0064] In a specific embodiment of the present invention, The setting value of is 0.35. The setting value of is 0.35. The setting value is 0.3. Temperature is one of the important factors affecting sleep quality. The most suitable temperature range for human body during sleep is 18℃-25℃. Within this range, human body will feel most comfortable and can get good sleep quality. Humidity is also an important factor affecting sleep comfort. The best relative humidity for human body to feel comfortable indoors is 49%~51%. If the relative humidity is too low or too high, human body will feel uncomfortable and even harmful to human body.

[0065] S4. Confirmation of user sleep stage: Collect the target user's turning over times in each monitoring time period on each sleep monitoring day, as well as the breathing rate and heart rate at each sampling point, to confirm the target user's sleep stage corresponding to each monitoring time period on each sleep monitoring day, where the sleep stage includes deep sleep and light sleep.

[0066] It should be noted that the number of times the target user turns over in each monitoring time period on each sleep monitoring day, as well as the breathing frequency and heart rate at each sampling point are extracted from the monitoring data of the target smart mattress.

[0067] In a specific embodiment of the present invention, the specific process of confirming the sleep stage corresponding to each monitoring time period of each sleep monitoring day of the target user is as follows: D1, based on the number of turning over of the target user in each monitoring time period of each sleep monitoring day and the breathing frequency and heart rate of each sampling point, the sleep quality index of the target user in each monitoring time period of each sleep monitoring day is calculated. .

[0068] In a specific embodiment of the present invention, the specific process of calculating the sleep quality index of the target user in each monitoring time period of each sleep monitoring day is as follows: E1, the number of turning over of the target user in each monitoring time period of each sleep monitoring day is recorded as .

[0069] E2. Using the sampling point as the horizontal coordinate and the breathing frequency as the vertical coordinate, a breathing frequency change curve of the target user in each monitoring time period of each sleep monitoring day is constructed, and the slope value is located from the curve as the breathing frequency change rate of the target user in each monitoring time period of each sleep monitoring day, which is marked as .

[0070] E3. Calculate the target user's breathing rate change during each monitoring period on each sleep monitoring day , ,in, Indicates the respiratory rate change rate of the set reference.

[0071] E4. Similarly, calculate the heart rate variation of the target user in each monitoring period on each sleep monitoring day .

[0072] E5. Calculate the target user's sleep quality index for each monitoring period on each sleep monitoring day , ,in, , and They represent the weights of sleep quality assessment corresponding to the set number of turning over, breathing rate change and heart rate change. , , and They respectively represent the set reference number of turning over, the comfort of the sleeping environment and the sleep quality compensated for the unit deviation of the sleeping environment comfort.

[0073] In a specific embodiment of the present invention, The setting value of is 0.3. The setting value of is 0.4. The setting value is 0.3. Respiratory frequency is an important indicator for measuring sleep quality. Normal respiratory frequency during sleep should be between 12 and 20 times per minute. The variability of respiratory frequency can reflect the stability and depth of sleep. For example, the respiratory frequency of patients with sleep apnea syndrome will fluctuate abnormally, which will affect sleep quality. Therefore, the variability of respiratory frequency is an important indicator for evaluating sleep quality.

[0074] The embodiment of the present invention analyzes the sleeping environment comfort of the target user corresponding to each monitoring time period of each sleep monitoring day in combination with the indoor temperature, indoor humidity and indoor light intensity, thereby correcting the impact on the sleep quality during the sleep process, improving the accuracy of the sleep quality analysis during the sleep process, and effectively solving the sleep problems of the target user. It can timely identify and improve the bad sleeping environment, thereby improving the user's sleep quality.

[0075] D2. Compare the target user's sleep quality index in each monitoring time period on each sleep monitoring day with the set reference sleep quality index, and record the monitoring time period when the sleep quality index is greater than or equal to the set reference sleep quality index as a deep sleep stage, otherwise, it is recorded as a light sleep stage, and count the number of deep sleep stages of the target user on each sleep monitoring day.

[0076] The embodiment of the present invention confirms the sleep stage of the target user corresponding to each monitoring time period on each sleep monitoring day by combining the number of times the target user turns over in each monitoring time period on each sleep monitoring day as well as the breathing frequency and heart rate at each sampling point. This can provide personalized sleep suggestions for the target user. For users with sleep disorders, it can help doctors or therapists develop more effective treatment plans, while comprehensively evaluating the health status of their sleep cycles, thereby providing effective intervention measures.

[0077] S5. Sleep quality analysis: Analyze the target user's sleep quality index during sleep, and compare and analyze whether the target user has sleep quality problems during sleep, and provide feedback.

[0078] In a specific embodiment of the present invention, the calculation formula of the sleep quality index of the target user during sleep is: ,in, Indicates the target user's sleep quality index during sleep. Indicates the number of deep sleep stages of the target user on each sleep monitoring day. Indicates the number of monitoring time periods. Indicates the number of sleep monitoring days. Indicates the percentage of deep sleep stage for setting reference.

[0079] It should be noted that the process of analyzing whether the target user has sleep quality problems during sleep is: comparing the sleep quality index of the target user during sleep with the sleep quality index of a set reference during sleep. If the sleep quality index of the target user during sleep is less than the sleep quality index of the set reference during sleep, it indicates that the target user has sleep quality problems during sleep.

[0080] S6. Comprehensive sleep quality analysis: Analyze the comprehensive sleep quality index of the target user, and compare and analyze whether the target user has sleep disorders, and provide feedback.

[0081] In a specific embodiment of the present invention, the calculation formula of the comprehensive sleep quality index of the target user is: ,in, Represents the comprehensive sleep quality index of the target user, and They represent the weights of the set difficulty falling asleep index and the sleep quality index during sleep corresponding to the comprehensive sleep quality assessment. .

[0082] In a specific embodiment of the present invention, The setting value of is 0.5. The setting value is 0.5.

[0083] It should be noted that the process of analyzing whether the target user has a sleep disorder is: comparing the target user's comprehensive sleep quality index with the set reference comprehensive sleep quality index. If the target user's comprehensive sleep quality index is less than the set reference comprehensive sleep quality index, it indicates that the target user has a sleep disorder.

[0084] The embodiment of the present invention comprehensively analyzes whether the target user has sleep disorders by combining whether the target user has difficulty falling asleep and whether the target user has sleep quality problems during sleep, thereby improving the comprehensiveness and accuracy of the evaluation of the target user's sleep problems, reducing the impact on the target user's physical and mental health, and improving the timeliness of the discovery and treatment of difficulty falling asleep.

[0085] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A method for analyzing human sleep data based on intelligent mattress monitoring, characterized in that: The steps include: S1. Sleeping state information collection: extract the time point corresponding to when the target user is ready to fall asleep on each sleep monitoring day, and collect the heart rate and breathing rate corresponding to each monitoring time point within a period of time after the target user is ready to fall asleep on each sleep monitoring day; S2. Analysis of difficulty falling asleep: Analyze the difficulty falling asleep of the target users, and compare and analyze whether the target users have difficulty falling asleep, and provide feedback; S3, sleep environment comfort analysis: collect the sleep environment information corresponding to each monitoring time period after the target user has entered the sleep state on each sleep monitoring day, and analyze the sleep environment comfort corresponding to each monitoring time period of the target user on each sleep monitoring day; S4, confirming the sleep stage of the user: collecting the number of times the target user turns over in each monitoring time period on each sleep monitoring day, as well as the breathing rate and heart rate at each sampling point, and confirming the sleep stage corresponding to each monitoring time period on each sleep monitoring day, wherein the sleep stage includes deep sleep and light sleep; S5. Sleep quality analysis: Analyze the target user's sleep quality index during sleep, and compare and analyze whether the target user has sleep quality problems during sleep, and provide feedback; S6. Comprehensive sleep quality analysis: Analyze the comprehensive sleep quality index of the target user, and compare and analyze whether the target user has sleep disorders, and provide feedback; According to the target user's difficulty falling asleep, a target user's difficulty falling asleep index is constructed and analyzed. The specific construction process is as follows: A1. According to the heart rate and breathing rate corresponding to each monitoring time point in a period of time after the target user prepares to fall asleep on each sleep monitoring day, determine the time point corresponding to the target user entering the sleep state on each sleep monitoring day; A2. Compare the time point when the target user enters the sleep state on each sleep monitoring day with the time point when the target user is ready to fall asleep, and obtain the target user's sleep duration on each sleep monitoring day, recorded as ,in, Indicates the number of the sleep monitoring day, ; A3. Calculate the target user's difficulty falling asleep index , ,in, and They represent the reference sleep duration and sleep duration deviation respectively. Indicates the number of sleep monitoring days. represents a natural constant; The specific process of confirming the time point corresponding to the target user entering the sleep state on each sleep monitoring day is as follows: B1. Record the heart rate and breathing rate of the target user at each monitoring time point within a period of time after they are ready to fall asleep on each sleep monitoring day as and ,in, Indicates the number of the monitoring time point, ; B2. Extract the corresponding reference heart rate and respiratory rate when entering the sleep state from the database and record them as and ; B3. Calculate the sleep stability of the target user at each monitoring time point within a period of time after the target user prepares to fall asleep on each sleep monitoring day. , ,in, and They represent the heart rate deviation and respiratory rate deviation of the set reference respectively. and They represent the weights of the set heart rate deviation and breathing frequency deviation corresponding to the sleep state stability assessment. ; B4, comparing the sleep state stability corresponding to each monitoring time point within a period of time after the target user prepares to fall asleep on each sleep monitoring day with the sleep state stability of the set reference, and recording the first monitoring time point corresponding to the target user's sleep state stability within a period of time after the target user prepares to fall asleep on each sleep monitoring day when it is greater than the sleep state stability of the set reference as the time point corresponding to entering the sleep state; The sleeping environment information includes indoor temperature, indoor humidity and indoor light intensity; The specific process of analyzing the target user's sleeping environment comfort level corresponding to each monitoring time period on each sleep monitoring day is as follows: C1. Extract the indoor temperature, indoor humidity and indoor light intensity from the sleep environment information corresponding to each monitoring period after the target user has entered the sleep state on each sleep monitoring day, and record them as , and ,in, Indicates the number of the monitoring time period. ; C2. Extract the appropriate indoor temperature, appropriate indoor humidity and appropriate indoor light intensity in the sleeping state from the database and record them as , and ; C3. Calculate the temperature suitability index, humidity suitability index and light suitability index of the target user in each monitoring period of each sleep monitoring day, and record them as , and ; C4. Calculate the target user's sleeping environment comfort level for each monitoring period on each sleep monitoring day , ,in, , and They represent the weights of the set temperature suitability index, humidity suitability index, and light suitability index corresponding to the comfort level of the sleeping environment. ; The calculation formula of the temperature suitability index corresponding to each monitoring time period of the target user on each sleep monitoring day is: ,in, Indicates the appropriate indoor temperature deviation from the set reference; The calculation formula for the humidity suitability index corresponding to each monitoring time period of the target user on each sleep monitoring day is: ,in, Indicates the indoor humidity deviation from the set reference; The calculation formula for the light suitability index of the target user corresponding to each monitoring time period on each sleep monitoring day is: ,in, Indicates the indoor light intensity deviation from the set reference; The specific process of confirming the target user's sleep stage corresponding to each monitoring time period on each sleep monitoring day is as follows: D1. Calculate the target user's sleep quality index for each monitoring period on each sleep monitoring day based on the target user's turning over times during each monitoring period on each sleep monitoring day, as well as the breathing rate and heart rate at each sampling point. ; D2. Compare the target user's sleep quality index in each monitoring time period on each sleep monitoring day with the set reference sleep quality index, and record the monitoring time period with a sleep quality index greater than or equal to the set reference sleep quality index as a deep sleep stage, otherwise, it is recorded as a light sleep stage, and count the number of deep sleep stages of the target user on each sleep monitoring day; The specific process of calculating the sleep quality index of the target user in each monitoring time period of each sleep monitoring day is as follows: E1. Record the number of times the target user turns over in each monitoring period on each sleep monitoring day as ; E2. Using the sampling point as the horizontal coordinate and the breathing frequency as the vertical coordinate, a breathing frequency change curve of the target user in each monitoring time period of each sleep monitoring day is constructed, and the slope value is located from the curve as the breathing frequency change rate of the target user in each monitoring time period of each sleep monitoring day, which is marked as ; E3. Calculate the target user's breathing rate change during each monitoring period on each sleep monitoring day , ,in, Indicates the respiratory rate change rate of the set reference; E4. Similarly, calculate the heart rate variation of the target user in each monitoring period on each sleep monitoring day ; E5. Calculate the target user's sleep quality index for each monitoring period on each sleep monitoring day , ,in, , and They represent the weights of sleep quality assessment corresponding to the set number of turning over, breathing rate change and heart rate change. , , and They represent the reference turning times, the comfort of the sleeping environment, and the sleep quality compensated for the unit deviation of the comfort of the sleeping environment; The calculation formula of the sleep quality index of the target user during sleep is: ,in, Indicates the target user's sleep quality index during sleep. Indicates the number of deep sleep stages of the target user on each sleep monitoring day. Indicates the number of monitoring time periods. Indicates the number of sleep monitoring days. Indicates the percentage of deep sleep stage for setting reference; The calculation formula of the comprehensive sleep quality index of the target user is: ,in, Represents the comprehensive sleep quality index of the target user, and They represent the weights of the set difficulty falling asleep index and the sleep quality index during sleep corresponding to the comprehensive sleep quality assessment. .

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