Sleep quality monitoring system and method based on multi-source data fusion

Abstract

The present application relates to the technical field of sleep quality monitoring, in particular to a sleep quality monitoring system and method based on multi-source data fusion, which is used to solve the problems that the monitoring results of the existing sleep quality monitoring methods are not accurate and comprehensive, the sleep quality of users cannot be comprehensively reflected, targeted sleep improvement suggestions cannot be provided according to individual differences of users, and the degree of intelligence is low; the system first collects the body sign related data and behavior related data of the monitoring object, can obtain more comprehensive and accurate sleep information through the fusion of multiple data, improves the accuracy of sleep state recognition, can more accurately evaluate the sleep quality, can also identify the factors affecting the sleep quality, provides personalized sleep improvement scheme for the user, helps the user to improve the sleep quality and improve the life quality; the system is suitable for family health management, medical rehabilitation, sleep scientific research and other fields, and has wide application prospect.

Description

Technical Field

[0001] This invention relates to the field of sleep quality monitoring technology, specifically to a sleep quality monitoring system and method based on multi-source data fusion. Background Technology

[0002] Sleep quality is crucial for physical and mental health. Good sleep helps restore physical strength, enhance immunity, and consolidate memory, while insufficient sleep or sleep disorders can lead to various health problems, such as cardiovascular disease, mental illness, and weakened immunity. Therefore, accurate monitoring and assessment of sleep quality has significant clinical and health management implications.

[0003] Currently, existing sleep quality monitoring methods suffer from limitations such as limited monitoring information and low accuracy. This results in inaccurate and incomplete monitoring results, failing to fully reflect the user's sleep quality and providing targeted sleep improvement suggestions based on individual differences. Furthermore, their level of intelligence is low.

[0004] Therefore, developing a sleep quality monitoring system and method based on multi-source data fusion is of great practical significance. Summary of the Invention

[0005] To overcome the aforementioned technical problems, the present invention aims to provide a sleep quality monitoring system and method based on multi-source data fusion, which solves the problems that existing sleep quality monitoring methods are not accurate and comprehensive enough, cannot fully reflect the user's sleep quality, cannot provide targeted sleep improvement suggestions based on the user's individual differences, and have a low level of intelligence.

[0006] The objective of this invention can be achieved through the following technical solutions:

[0007] A sleep quality monitoring system based on multi-source data fusion includes the following modules:

[0008] The data analysis module is used to obtain the vital sign detection coefficient based on the vital sign detection parameters and send the vital sign detection coefficient to the quality assessment module; it is also used to obtain the vital sign sleep assessment coefficient based on the determination of non-sleep period and sleep period; it is also used to obtain the behavioral sleep assessment coefficient based on the behavioral detection parameters, and obtain the sleep assessment index based on the vital sign sleep assessment coefficient and the behavioral sleep assessment coefficient, and send the sleep assessment index to the quality assessment module.

[0009] The quality assessment module is used to determine non-sleep periods and sleep periods based on vital sign detection coefficients, and then sends the determined non-sleep periods and sleep periods to the data analysis module; it is also used to assess sleep quality based on the sleep assessment index.

[0010] In a preferred embodiment of the present invention, the specific process by which the data analysis module obtains the vital sign detection coefficients is as follows:

[0011] The heart rate, respiration, blood pressure and brain wave information are quantified. The values ​​of heart rate, respiration, blood pressure and brain wave information are multiplied by their respective preset weight factors. The sum of the four is then obtained and marked as the vital sign detection coefficient.

[0012] Send the vital signs detection coefficients to the quality assessment module.

[0013] In a preferred embodiment of the present invention, the specific process by which the data analysis module obtains the vital signs sleep assessment coefficient is as follows:

[0014] Obtain the total number of sleep periods identified and mark them as relapse information;

[0015] Obtain the total duration of non-sleep periods and the total duration of sleep periods, obtain the ratio between the two, and mark it as sleep ratio information;

[0016] Obtain the product of resuscitation information and sleep ratio information, and label it as the vital signs sleep assessment coefficient.

[0017] In a preferred embodiment of the present invention, the specific process by which the data analysis module obtains the sleep assessment index is as follows:

[0018] The body movement information and swallowing information are quantified. The values ​​of body movement information and swallowing information are multiplied by their corresponding preset ratio coefficients, and then the sum of the two is obtained and marked as the behavioral sleep assessment coefficient.

[0019] The vital signs sleep assessment coefficient is scaled according to the corresponding preset ratio and marked as the vital signs sleep regulation value;

[0020] The behavioral sleep assessment coefficient is scaled according to the corresponding preset ratio and marked as the behavioral sleep regulation value;

[0021] Using the values ​​of vital signs sleep regulation value and behavioral sleep regulation value as the major and minor axes of the ellipse, respectively, an ellipse was drawn, the area of ​​the ellipse was obtained, and it was marked as the sleep assessment index.

[0022] Send the sleep assessment index to the quality assessment module.

[0023] In a preferred embodiment of the present invention, the specific process by which the quality assessment module determines non-sleep periods and sleep periods is as follows:

[0024] The vital sign detection coefficients were compared with the preset vital sign detection thresholds. The comparison results are shown below:

[0025] Obtain the time period when the vital sign detection coefficient is greater than the vital sign detection threshold, and mark it as a non-sleep period.

[0026] Obtain the time period where the vital sign detection coefficient is ≤ the vital sign detection threshold, and mark it as the sleep period for determination;

[0027] The data will be sent to the data analysis module to determine whether the period is not sleep or whether the period is sleep.

[0028] In a preferred embodiment of the present invention, the specific process by which the quality assessment module assesses sleep quality is as follows:

[0029] The sleep assessment index was compared with the preset sleep assessment grading values, which included the first segment sleep assessment value and the second segment sleep assessment value. The comparison results are shown below:

[0030] If the sleep assessment index is greater than the first segment sleep assessment value, the control display will show the words "low quality sleep" and generate an environmental detection command, which will then be sent to the environmental detection module.

[0031] If the second segment sleep assessment value ≤ sleep assessment index ≤ first segment sleep assessment value, then the control display screen will show the words "Medium quality sleep";

[0032] If the sleep assessment index is less than the second segment sleep assessment value, the control display screen will show the words "high-quality sleep".

[0033] In a preferred embodiment of the present invention, the sleep quality monitoring system further includes:

[0034] The vital signs detection module is used to acquire the vital signs detection parameters of the monitored object and send the vital signs detection parameters to the data analysis module; wherein, the vital signs detection parameters include heart rate information, respiratory information, blood pressure information and brain wave information.

[0035] In a preferred embodiment of the present invention, the specific process by which the vital sign detection module acquires vital sign detection parameters is as follows:

[0036] Those who conduct sleep quality monitoring will be marked as monitoring subjects;

[0037] The system obtains the real-time heart rate and the preset standard heart rate of the monitored object within a preset monitoring period, obtains the difference between the two, and marks it as heart rate information.

[0038] The system obtains the real-time respiratory rate and the preset standard respiratory rate of the monitored object within a preset monitoring period, obtains the difference between the two, and marks it as respiratory information.

[0039] The system obtains the real-time systolic blood pressure and the preset standard systolic blood pressure of the monitored subject within a preset monitoring period, obtains the difference between the two and marks it as the systolic blood pressure value, obtains the real-time diastolic blood pressure and the preset standard diastolic blood pressure of the monitored subject within a preset monitoring period, obtains the difference between the two and marks it as the systolic blood pressure value, obtains the average value between the systolic blood pressure value and the systolic blood pressure value and marks it as blood pressure information.

[0040] The real-time EEG frequency and the preset standard EEG frequency of the monitored object within the preset monitoring time period are obtained, the difference between the two is obtained, and it is marked as EEG information.

[0041] Heart rate, respiration, blood pressure, and brain wave information are sent to the data analysis module.

[0042] In a preferred embodiment of the present invention, the sleep quality monitoring system further includes:

[0043] The behavior detection module is used to acquire the behavior detection parameters of the monitored object and send the behavior detection parameters to the data analysis module; wherein, the behavior detection parameters include body movement information and swallowing information.

[0044] In a preferred embodiment of the present invention, the specific process by which the behavior detection module acquires behavior detection parameters is as follows:

[0045] The total number of times that the movement rate of a preset body part of the monitored object is greater than the preset movement rate within a preset monitoring time period is obtained and marked as body movement information.

[0046] The number of swallows in the pharynx of the monitored subject within a preset monitoring time period is obtained and marked as swallowing information;

[0047] The body movement and swallowing information are sent to the data analysis module.

[0048] In a preferred embodiment of the present invention, the sleep quality monitoring system further includes:

[0049] The environmental monitoring module is used to acquire environmental monitoring parameters of the monitored object and send the environmental monitoring parameters to the data analysis module; wherein, the environmental monitoring parameters include temperature information, humidity information, sound information and light information.

[0050] In a preferred embodiment of the present invention, the specific process by which the environmental detection module acquires environmental detection parameters is as follows:

[0051] Upon receiving an environmental monitoring command, the system obtains the temperature of the environment in which the monitored object is located and the preset standard temperature, calculates the difference between the two, and marks it as temperature information.

[0052] The humidity of the environment where the monitored object is located and the preset standard humidity are obtained. The difference between the two is then marked as humidity information.

[0053] The sound intensity of the environment where the monitored object is located and the preset standard sound intensity are obtained. The difference between the two is then marked as sound information.

[0054] The light intensity of the environment where the monitored object is located and the preset standard light intensity are obtained. The difference between the two is then marked as light information.

[0055] Temperature, humidity, sound, and light information are sent to the data analysis module.

[0056] In a preferred embodiment of the present invention, the data analysis module is further configured to obtain an environmental assessment coefficient based on environmental monitoring parameters and send the environmental assessment coefficient to the quality assessment module.

[0057] In a preferred embodiment of the present invention, the specific process by which the data analysis module obtains the environmental assessment coefficient is as follows:

[0058] The temperature information is scaled according to the corresponding preset ratio and marked as temperature adjustment information;

[0059] The humidity information is scaled according to the corresponding preset ratio and marked as humidity adjustment information;

[0060] The sound information is scaled according to the corresponding preset ratio and marked as sound adjustment information;

[0061] The illumination information is scaled according to the corresponding preset ratio and marked as illumination adjustment information;

[0062] The temperature regulation information, humidity regulation information, sound regulation information, and light regulation information are quantified. The values ​​of temperature regulation information, humidity regulation information, sound regulation information, and light regulation information are multiplied by their corresponding preset proportional coefficients, and then the sum of the four is obtained and marked as the environmental assessment coefficient.

[0063] Send the environmental assessment coefficients to the quality assessment module.

[0064] In a preferred embodiment of the present invention, the quality assessment module is further configured to generate environmental control instructions based on environmental assessment coefficients and send the environmental control instructions to the environmental control module.

[0065] In a preferred embodiment of the present invention, the specific process by which the quality assessment module generates environmental control instructions is as follows:

[0066] The environmental assessment coefficients were compared with the preset environmental assessment thresholds, and the comparison results are shown below:

[0067] If the environmental assessment coefficient is greater than or equal to the environmental assessment threshold, an environmental control instruction is generated and sent to the environmental control module.

[0068] In a preferred embodiment of the present invention, the sleep quality monitoring system further includes:

[0069] The environmental control module is used to adjust the environment in which the monitored object is located according to standard environmental parameters.

[0070] As a preferred embodiment of the present invention, the sleep quality monitoring method based on multi-source data fusion includes the following steps:

[0071] Step s1: The vital signs detection module acquires the vital signs detection parameters of the monitored object, wherein the vital signs detection parameters include heart rate information, respiratory information, blood pressure information and brain wave information, and sends the vital signs detection parameters to the data analysis module;

[0072] Step s2: The data analysis module obtains the vital sign detection coefficients based on the vital sign detection parameters and sends the vital sign detection coefficients to the quality assessment module;

[0073] Step s3: The quality assessment module obtains the determination of non-sleep periods and sleep periods based on the vital sign detection coefficients, and sends the determination of non-sleep periods and sleep periods to the data analysis module;

[0074] Step s4: The data analysis module obtains the vital signs sleep assessment coefficient based on the determination of non-sleep periods and sleep periods;

[0075] Step s5: The behavior detection module acquires the behavior detection parameters of the monitored object, wherein the behavior detection parameters include body movement information and swallowing information, and sends the behavior detection parameters to the data analysis module;

[0076] Step s6: The data analysis module obtains the behavioral sleep assessment coefficient based on the behavioral detection parameters, and obtains the sleep assessment index based on the physical sign sleep assessment coefficient and the behavioral sleep assessment coefficient, and sends the sleep assessment index to the quality assessment module.

[0077] Step s7: The quality assessment module assesses sleep quality based on the sleep assessment index;

[0078] Step s8: The environmental detection module acquires the environmental detection parameters of the monitored object, including temperature information, humidity information, sound information and light information, and sends the environmental detection parameters to the data analysis module;

[0079] Step s9: The data analysis module obtains the environmental assessment coefficient based on the environmental monitoring parameters and sends the environmental assessment coefficient to the quality assessment module;

[0080] Step s10: The quality assessment module generates environmental control instructions based on the environmental assessment coefficients and sends the environmental control instructions to the environmental control module;

[0081] Step s11: The environmental control module adjusts the environment of the monitored object according to standard environmental parameters.

[0082] Compared with the prior art, the beneficial effects of the present invention are:

[0083] This system can comprehensively measure a user's sleep quality through the vital signs sleep assessment coefficient and the behavioral sleep assessment coefficient. The sleep assessment index obtained from these two factors can accurately assess a user's sleep quality, and the higher the sleep assessment index, the worse the sleep quality. Finally, when the sleep quality is poor, data on the sleep environment is collected, and the collected data is comprehensively processed to obtain an environmental assessment coefficient, which can comprehensively measure the degree of influence of environmental factors. The higher the environmental assessment coefficient, the greater the influence of environmental factors on sleep quality, and finally, intelligent adjustment is performed.

[0084] The system first collects vital signs and behavioral data of the monitored subjects. By integrating multiple data sources, it can obtain more comprehensive and accurate sleep information, improve the accuracy of sleep state identification, more accurately assess sleep quality, and identify factors that affect sleep quality. It can also provide users with personalized sleep improvement plans, helping them improve their sleep quality and quality of life. The system is applicable to multiple fields such as family health management, medical rehabilitation, and sleep science research, and has broad application prospects. Attached Figure Description

[0085] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0086] Figure 1 This is a block diagram illustrating the principle of the sleep quality monitoring system based on multi-source data fusion according to the present invention.

[0087] Figure 2 This is a flowchart of the sleep quality monitoring method based on multi-source data fusion according to the present invention. Detailed Implementation

[0088] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0089] Example 1:

[0090] Please see Figure 1 As shown, this embodiment is a sleep quality monitoring system based on multi-source data fusion, including the following modules: vital sign detection module, data analysis module, quality assessment module, behavior detection module, environmental detection module, and environmental control module;

[0091] The vital signs detection module is used to acquire the vital signs detection parameters of the monitored object and send the vital signs detection parameters to the data analysis module; wherein, the vital signs detection parameters include heart rate information, respiratory information, blood pressure information and brain wave information;

[0092] The data analysis module is used to obtain vital sign detection coefficients based on vital sign detection parameters and send these coefficients to the quality assessment module; it is also used to obtain vital sign sleep assessment coefficients based on the determination of non-sleep periods and sleep periods; it is also used to obtain behavioral sleep assessment coefficients based on behavioral detection parameters, and to obtain a sleep assessment index based on the vital sign sleep assessment coefficients and behavioral sleep assessment coefficients, and send the sleep assessment index to the quality assessment module; it is also used to obtain environmental assessment coefficients based on environmental detection parameters and send these coefficients to the quality assessment module.

[0093] The quality assessment module is used to determine non-sleep periods and sleep periods based on vital sign detection coefficients, and send the determined non-sleep periods and sleep periods to the data analysis module; it is also used to assess sleep quality based on the sleep assessment index; and it is also used to generate environmental control instructions based on the environmental assessment coefficients, and send the environmental control instructions to the environmental control module.

[0094] The behavior detection module is used to acquire behavior detection parameters of the monitored object and send the behavior detection parameters to the data analysis module; wherein, the behavior detection parameters include body movement information and swallowing information;

[0095] An environmental monitoring module is used to acquire environmental monitoring parameters of the monitored object and send these parameters to a data analysis module; wherein, the environmental monitoring parameters include temperature information, humidity information, sound information, and light information;

[0096] The environmental control module is used to adjust the environment in which the monitored object is located according to standard environmental parameters.

[0097] Example 2:

[0098] Please see Figure 2 As shown, this embodiment is a sleep quality monitoring method based on multi-source data fusion, including the following steps:

[0099] Step s1: The vital signs detection module acquires the vital signs detection parameters of the monitored object, wherein the vital signs detection parameters include heart rate information, respiratory information, blood pressure information and brain wave information, and sends the vital signs detection parameters to the data analysis module;

[0100] Step s2: The data analysis module obtains the vital sign detection coefficients based on the vital sign detection parameters and sends the vital sign detection coefficients to the quality assessment module;

[0101] Step s3: The quality assessment module obtains the determination of non-sleep periods and sleep periods based on the vital sign detection coefficients, and sends the determination of non-sleep periods and sleep periods to the data analysis module;

[0102] Step s4: The data analysis module obtains the vital signs sleep assessment coefficient based on the determination of non-sleep periods and sleep periods;

[0103] Step s5: The behavior detection module acquires the behavior detection parameters of the monitored object, wherein the behavior detection parameters include body movement information and swallowing information, and sends the behavior detection parameters to the data analysis module;

[0104] Step s6: The data analysis module obtains the behavioral sleep assessment coefficient based on the behavioral detection parameters, and obtains the sleep assessment index based on the physical sign sleep assessment coefficient and the behavioral sleep assessment coefficient, and sends the sleep assessment index to the quality assessment module.

[0105] Step s7: The quality assessment module assesses sleep quality based on the sleep assessment index;

[0106] Step s8: The environmental detection module acquires the environmental detection parameters of the monitored object, including temperature information, humidity information, sound information and light information, and sends the environmental detection parameters to the data analysis module;

[0107] Step s9: The data analysis module obtains the environmental assessment coefficient based on the environmental monitoring parameters and sends the environmental assessment coefficient to the quality assessment module;

[0108] Step s10: The quality assessment module generates environmental control instructions based on the environmental assessment coefficients and sends the environmental control instructions to the environmental control module;

[0109] Step s11: The environmental control module adjusts the environment of the monitored object according to standard environmental parameters.

[0110] Example 3:

[0111] Based on any of the above embodiments, Embodiment 3 of the present invention is a vital sign detection module. The function of the vital sign detection module is to obtain vital sign detection parameters, and the specific process is as follows:

[0112] The vital signs detection module marks individuals undergoing sleep quality monitoring as monitoring subjects;

[0113] The vital signs detection module obtains the real-time heart rate and the preset standard heart rate of the monitored object within a preset monitoring time period, obtains the difference between the two, and marks it as heart rate information;

[0114] The vital signs detection module obtains the real-time respiratory rate and the preset standard respiratory rate of the monitored object within a preset monitoring period, obtains the difference between the two, and marks it as respiratory information;

[0115] The vital signs detection module obtains the real-time systolic blood pressure and the preset standard systolic blood pressure of the monitored subject within a preset monitoring period, obtains the difference between the two and marks it as the systolic blood pressure value, obtains the real-time diastolic blood pressure and the preset standard diastolic blood pressure of the monitored subject within a preset monitoring period, obtains the difference between the two and marks it as the systolic blood pressure value, obtains the average value between the systolic blood pressure value and the systolic blood pressure value and marks it as blood pressure information;

[0116] The vital signs detection module obtains the real-time EEG frequency and the preset standard EEG frequency of the monitored object within a preset monitoring time period, obtains the difference between the two, and marks it as EEG information.

[0117] The vital signs detection module sends heart rate, respiration, blood pressure, and brain wave information to the data analysis module.

[0118] Example 4:

[0119] Based on any of the above embodiments, Embodiment 4 of the present invention is a data analysis module, which has four functions;

[0120] One of its purposes is to obtain the vital sign detection coefficient, and the specific process is as follows:

[0121] The data analysis module quantifies heart rate, respiration, blood pressure, and brain wave information. It multiplies the values ​​of each information by their respective preset weighting factors, then sums the results and labels this sum as the vital sign detection coefficient. The preset weighting factors for heart rate, respiration, blood pressure, and brain wave information are all set by the user based on experience, with the weighting factors decreasing sequentially but all being greater than 1.835. For example, the user might set the preset weighting factors for heart rate, respiration, blood pressure, and brain wave information to 3.72, 3.06, 2.35, and 1.98, respectively.

[0122] The data analysis module sends the vital sign detection coefficients to the quality assessment module;

[0123] The second purpose is to obtain the vital signs and sleep assessment coefficient, and the specific process is as follows:

[0124] The data analysis module obtains the total number of sleep periods and marks them as sleep relapse information;

[0125] The data analysis module obtains the total duration of non-sleep periods and the total duration of sleep periods, gets the ratio between the two, and marks it as sleep ratio information;

[0126] The data analysis module obtains the product of resuscitation information and sleep ratio information, and marks it as the vital signs sleep assessment coefficient;

[0127] The third purpose is to obtain a sleep assessment index, and the specific process is as follows:

[0128] The data analysis module quantifies the body movement and swallowing information, multiplying each value by its corresponding preset proportional coefficient, and then summing the two values ​​to obtain the behavioral sleep assessment coefficient. The preset proportional coefficients for body movement and swallowing information are set by the user based on experience, and these coefficients decrease sequentially and are both between 0 and 1, with a sum of 1. For example, the user might set the preset proportional coefficients for body movement and swallowing information to 0.61 and 0.39 respectively based on experience.

[0129] The data analysis module scales the vital signs and sleep assessment coefficients according to the corresponding preset ratios and marks them as vital signs and sleep adjustment values; the preset ratios corresponding to the vital signs and sleep assessment coefficients are set by the user based on experience, and none of them are zero.

[0130] The data analysis module scales the behavioral sleep assessment coefficients according to the corresponding preset ratios and marks them as behavioral sleep adjustment values; the preset ratios corresponding to the behavioral sleep assessment coefficients are set by the user based on experience, and none of them are zero.

[0131] The data analysis module uses the values ​​of vital signs sleep regulation value and behavioral sleep regulation value as the major and minor axes of the ellipse to draw an ellipse, obtains the area of ​​the ellipse, and marks it as the sleep assessment index.

[0132] The data analysis module sends the sleep assessment index to the quality assessment module;

[0133] The fourth function is to obtain environmental assessment coefficients, and the specific process is as follows:

[0134] The data analysis module scales the temperature information according to a preset ratio and marks it as temperature adjustment information; the preset ratio corresponding to the temperature information is set by the user based on experience, and none of them are zero.

[0135] The data analysis module scales the humidity information according to a preset ratio and marks it as humidity adjustment information; the preset ratio corresponding to the humidity information is set by the user based on experience, and none of them are zero.

[0136] The data analysis module scales the sound information according to a preset ratio and marks it as sound adjustment information; the preset ratio corresponding to the sound information is set by the user based on experience, and none of them are zero.

[0137] The data analysis module scales the illumination information according to the corresponding preset ratio and marks it as illumination adjustment information; the preset ratio corresponding to the illumination information is set by the user based on experience, and none of them are zero.

[0138] The data analysis module quantifies the temperature, humidity, sound, and light regulation information. It multiplies each value by its corresponding preset proportional coefficient, then sums the results to obtain the environmental assessment coefficient. The preset proportional coefficients for temperature, humidity, sound, and light regulation are set by the user based on experience. These coefficients decrease sequentially and are all between 0 and 1, with a sum of 1. For example, the user might set the preset proportional coefficients to 0.38, 0.28, 0.25, and 0.09 respectively.

[0139] The data analysis module sends the environmental assessment coefficients to the quality assessment module.

[0140] Example 5:

[0141] Based on any of the above embodiments, Embodiment 5 of the present invention is a quality assessment module, which has three functions;

[0142] One of its functions is to determine non-sleep periods and sleep periods. The specific process is as follows:

[0143] The quality assessment module compares the vital sign detection coefficients with preset vital sign detection thresholds. The comparison results are shown below:

[0144] The quality assessment module obtains the time periods when the vital sign detection coefficient is greater than the vital sign detection threshold and marks them as non-sleep periods.

[0145] The quality assessment module obtains the time periods when the vital sign detection coefficient is ≤ the vital sign detection threshold and marks them as sleep periods.

[0146] The quality assessment module will send the determination of non-sleep periods and sleep periods to the data analysis module;

[0147] The second purpose is to assess sleep quality, and the specific process is as follows:

[0148] The quality assessment module compares the sleep assessment index with preset sleep assessment grading values, which include a first-segment sleep assessment value and a second-segment sleep assessment value. The comparison results are shown below:

[0149] If the sleep assessment index is greater than the first segment sleep assessment value, the control display will show the words "low quality sleep" and generate an environmental detection command, which will then be sent to the environmental detection module.

[0150] If the second segment sleep assessment value ≤ sleep assessment index ≤ first segment sleep assessment value, then the control display screen will show the words "Medium quality sleep";

[0151] If the sleep assessment index is less than the second segment sleep assessment value, the control display will show the words "high-quality sleep";

[0152] Its third function is to generate environmental control instructions, and the specific process is as follows:

[0153] The quality assessment module compares the environmental assessment coefficient with the preset environmental assessment threshold. The comparison results are shown below:

[0154] If the environmental assessment coefficient is greater than or equal to the environmental assessment threshold, an environmental control instruction is generated and sent to the environmental control module.

[0155] Example 6:

[0156] Based on any of the above embodiments, Embodiment 6 of the present invention is a behavior detection module. The function of the behavior detection module is to obtain behavior detection parameters, and the specific process is as follows:

[0157] The behavior detection module obtains the total number of times that the movement rate of a preset body part of the monitored object is greater than the preset movement rate within a preset monitoring time period, and marks it as body movement information.

[0158] The behavior detection module acquires the number of times the monitored object swallows within a preset monitoring time period and marks them as swallowing information.

[0159] The behavior detection module sends body movement and swallowing information to the data analysis module.

[0160] Example 7:

[0161] Based on any of the above embodiments, Embodiment 7 of the present invention is an environmental detection module. The function of the environmental detection module is to acquire environmental detection parameters, and the specific process is as follows:

[0162] After receiving the environmental monitoring command, the environmental monitoring module obtains the temperature of the environment where the monitored object is located and the preset standard temperature, obtains the difference between the two, and marks it as temperature information;

[0163] The environmental monitoring module obtains the humidity of the environment where the monitored object is located and the preset standard humidity, obtains the difference between the two, and marks it as humidity information;

[0164] The environmental detection module acquires the sound intensity of the environment in which the monitored object is located and the preset standard sound intensity, obtains the difference between the two, and marks it as sound information;

[0165] The environmental monitoring module obtains the light intensity of the environment where the monitored object is located and the preset standard light intensity, obtains the difference between the two, and marks it as light information;

[0166] The environmental monitoring module sends temperature, humidity, sound, and light information to the data analysis module.

[0167] Example 8:

[0168] Based on any of the above embodiments, Embodiment 8 of the present invention is an environmental control module. The function of the environmental control module is to adjust the environment in which the monitored object is located. The specific process is as follows:

[0169] After receiving the environmental control instruction, the environmental control module adjusts the environment of the monitored object according to the standard environmental parameters until the environmental assessment coefficient is less than the environmental assessment threshold. The standard environmental parameters include standard temperature, standard humidity, standard sound intensity, and standard light intensity.

[0170] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0171] The above description is merely an example and illustration of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described or use similar methods to replace them, as long as they do not deviate from the invention or exceed the scope defined in this application, they should all fall within the protection scope of the present invention.

Claims

1. A sleep quality monitoring system based on multi-source data fusion, characterized in that, Includes the following modules: The data analysis module is used to obtain the vital sign detection coefficient based on the vital sign detection parameters; it is also used to obtain the vital sign sleep assessment coefficient based on the determination of non-sleep periods and sleep periods; it is also used to obtain the behavioral sleep assessment coefficient based on the behavioral detection parameters, and to obtain the sleep assessment index based on the vital sign sleep assessment coefficient and the behavioral sleep assessment coefficient. The specific process by which the data analysis module obtains the vital sign detection coefficients is as follows: The heart rate, respiration, blood pressure and brain wave information are quantified. The values ​​of heart rate, respiration, blood pressure and brain wave information are multiplied by their respective preset weight factors. The sum of the four is then obtained and marked as the vital sign detection coefficient. Send the vital signs detection coefficients to the quality assessment module; The specific process by which the data analysis module obtains the vital signs sleep assessment coefficient is as follows: Obtain the total number of sleep periods identified and mark them as relapse information; Obtain the total duration of non-sleep periods and the total duration of sleep periods, obtain the ratio between the two, and mark it as sleep ratio information; Obtain the product of resuscitation information and sleep ratio information, and label it as the vital signs sleep assessment coefficient; The specific process by which the data analysis module obtains the sleep assessment index is as follows: The body movement information and swallowing information are quantified. The values ​​of body movement information and swallowing information are multiplied by their corresponding preset ratio coefficients, and then the sum of the two is obtained and marked as the behavioral sleep assessment coefficient. The vital signs sleep assessment coefficient is scaled according to the corresponding preset ratio and marked as the vital signs sleep regulation value; The behavioral sleep assessment coefficient is scaled according to the corresponding preset ratio and marked as the behavioral sleep regulation value; The sleep assessment index is obtained based on the sleep regulation values ​​of physical signs and the sleep regulation values ​​of behavior. Send the sleep assessment index to the quality assessment module; The quality assessment module is used to determine non-sleep periods and sleep periods based on vital sign detection coefficients. It is also used to assess sleep quality based on the sleep assessment index; The specific process by which the quality assessment module determines non-sleep periods and sleep periods is as follows: The vital sign detection coefficients were compared with the preset vital sign detection thresholds. The comparison results are shown below: Obtain the time period when the vital sign detection coefficient is greater than the vital sign detection threshold, and mark it as a non-sleep period. Obtain the time period where the vital sign detection coefficient is ≤ the vital sign detection threshold, and mark it as the sleep period for determination; The data will be sent to the data analysis module to determine whether the period is not sleep or whether the period is sleep.

2. The sleep quality monitoring system based on multi-source data fusion according to claim 1, characterized in that, The specific process by which the quality assessment module assesses sleep quality is as follows: The sleep assessment index was compared with the preset sleep assessment grading values, which included the first segment sleep assessment value and the second segment sleep assessment value. The comparison results are shown below: If the sleep assessment index is greater than the first segment sleep assessment value, the control display will show the words "low quality sleep", and an environmental detection command will be generated and sent to the environmental detection module. If the second segment sleep assessment value ≤ sleep assessment index ≤ first segment sleep assessment value, then the control display screen will show the words "Medium quality sleep"; If the sleep assessment index is less than the second segment sleep assessment value, the control display screen will show the words "high-quality sleep".

3. The sleep quality monitoring system based on multi-source data fusion according to claim 1, characterized in that, Also includes: The vital signs detection module is used to acquire the vital signs detection parameters of the monitored object and send the vital signs detection parameters to the data analysis module; wherein, the vital signs detection parameters include heart rate information, respiratory information, blood pressure information and brain wave information; The specific process by which the vital sign detection module acquires vital sign detection parameters is as follows: Those who conduct sleep quality monitoring will be marked as monitoring subjects; The system obtains the real-time heart rate and the preset standard heart rate of the monitored object within a preset monitoring period, obtains the difference between the two, and marks it as heart rate information. The system obtains the real-time respiratory rate and the preset standard respiratory rate of the monitored object within a preset monitoring period, obtains the difference between the two, and marks it as respiratory information. The system obtains the real-time systolic blood pressure and the preset standard systolic blood pressure of the monitored subject within a preset monitoring period, obtains the difference between the two and marks it as the systolic blood pressure value, obtains the real-time diastolic blood pressure and the preset standard diastolic blood pressure of the monitored subject within a preset monitoring period, obtains the difference between the two and marks it as the systolic blood pressure value, obtains the average value between the systolic blood pressure value and the systolic blood pressure value and marks it as blood pressure information. The real-time EEG frequency and the preset standard EEG frequency of the monitored object within the preset monitoring time period are obtained, the difference between the two is obtained, and it is marked as EEG information. Heart rate, respiration, blood pressure, and brain wave information are sent to the data analysis module.

4. The sleep quality monitoring system based on multi-source data fusion according to claim 1, characterized in that, Also includes: The behavior detection module is used to acquire behavior detection parameters of the monitored object and send the behavior detection parameters to the data analysis module; wherein, the behavior detection parameters include body movement information and swallowing information; The specific process by which the behavior detection module obtains behavior detection parameters is as follows: The total number of times that the movement rate of a preset body part of the monitored object is greater than the preset movement rate within a preset monitoring time period is obtained and marked as body movement information. The number of swallows in the pharynx of the monitored subject within a preset monitoring time period is obtained and marked as swallowing information; The body movement and swallowing information are sent to the data analysis module.

5. The sleep quality monitoring system based on multi-source data fusion according to claim 1, characterized in that, Also includes: An environmental monitoring module is used to acquire environmental monitoring parameters of the monitored object and send these parameters to a data analysis module; wherein, the environmental monitoring parameters include temperature information, humidity information, sound information, and light information; The specific process by which the environmental monitoring module acquires environmental monitoring parameters is as follows: Upon receiving an environmental monitoring command, the system obtains the temperature of the environment in which the monitored object is located and the preset standard temperature, calculates the difference between the two, and marks it as temperature information. The humidity of the environment where the monitored object is located and the preset standard humidity are obtained. The difference between the two is then marked as humidity information. The sound intensity of the environment where the monitored object is located and the preset standard sound intensity are obtained. The difference between the two is then marked as sound information. The light intensity of the environment where the monitored object is located and the preset standard light intensity are obtained. The difference between the two is then marked as light information. Temperature, humidity, sound, and light information are sent to the data analysis module.

6. The sleep quality monitoring system based on multi-source data fusion according to claim 5, characterized in that, The data analysis module is also used to obtain environmental assessment coefficients based on environmental monitoring parameters and send the environmental assessment coefficients to the quality assessment module. The specific process by which the data analysis module obtains the environmental assessment coefficients is as follows: The temperature information is scaled according to the corresponding preset ratio and marked as temperature adjustment information; The humidity information is scaled according to the corresponding preset ratio and marked as humidity adjustment information; The sound information is scaled according to the corresponding preset ratio and marked as sound adjustment information; The illumination information is scaled according to the corresponding preset ratio and marked as illumination adjustment information; The environmental assessment coefficient is obtained by quantifying the temperature regulation information, humidity regulation information, sound regulation information, and light regulation information. Send the environmental assessment coefficients to the quality assessment module.

7. The sleep quality monitoring system based on multi-source data fusion according to claim 6, characterized in that, The quality assessment module is also used to generate environmental control instructions based on environmental assessment coefficients and send the environmental control instructions to the environmental control module. The specific process by which the quality assessment module generates environmental control instructions is as follows: The environmental assessment coefficients were compared with the preset environmental assessment thresholds, and the comparison results are shown below: If the environmental assessment coefficient is greater than or equal to the environmental assessment threshold, an environmental control instruction is generated and sent to the environmental control module.

8. The sleep quality monitoring system based on multi-source data fusion according to claim 7, characterized in that, Also includes: The environmental control module is used to adjust the environment in which the monitored object is located according to standard environmental parameters.

9. The sleep quality monitoring method of the sleep quality monitoring system based on multi-source data fusion as described in any one of claims 1-8, characterized in that, Includes the following steps: Step s1: The vital signs detection module acquires the vital signs detection parameters of the monitored object, wherein the vital signs detection parameters include heart rate information, respiratory information, blood pressure information and brain wave information, and sends the vital signs detection parameters to the data analysis module; Step s2: The data analysis module obtains the vital sign detection coefficients based on the vital sign detection parameters and sends the vital sign detection coefficients to the quality assessment module; Step s3: The quality assessment module obtains the determination of non-sleep periods and sleep periods based on the vital sign detection coefficients, and sends the determination of non-sleep periods and sleep periods to the data analysis module; Step s4: The data analysis module obtains the vital signs sleep assessment coefficient based on the determination of non-sleep periods and sleep periods; Step s5: The behavior detection module acquires the behavior detection parameters of the monitored object, wherein the behavior detection parameters include body movement information and swallowing information, and sends the behavior detection parameters to the data analysis module; Step s6: The data analysis module obtains the behavioral sleep assessment coefficient based on the behavioral detection parameters, and obtains the sleep assessment index based on the physical sign sleep assessment coefficient and the behavioral sleep assessment coefficient, and sends the sleep assessment index to the quality assessment module. Step s7: The quality assessment module assesses sleep quality based on the sleep assessment index; Step s8: The environmental detection module acquires the environmental detection parameters of the monitored object, including temperature information, humidity information, sound information and light information, and sends the environmental detection parameters to the data analysis module; Step s9: The data analysis module obtains the environmental assessment coefficient based on the environmental monitoring parameters and sends the environmental assessment coefficient to the quality assessment module; Step s10: The quality assessment module generates environmental control instructions based on the environmental assessment coefficients and sends the environmental control instructions to the environmental control module; Step s11: The environmental control module adjusts the environment of the monitored object according to standard environmental parameters.

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