CN116350179A - A method and system for monitoring physiological parameters of sleep based on intelligent sensing - Google Patents

Abstract

The invention discloses a sleep physiological parameter monitoring method and system based on intelligent sensing, and relates to the technical field of body monitoring, wherein the method comprises the following steps: acquiring a history sleep monitoring record and obtaining first monitoring data; extracting first sleep-in monitoring data; acquiring a preset physiological parameter set, and screening to obtain a first parameter set; monitoring a target user based on the first parameter set to obtain sleeping parameter information; judging whether the preset sleep condition is met, if so, extracting first formal sleep monitoring data and obtaining a second parameter set; obtaining formal sleep parameter information based on the second parameter set; and carrying out sleep quality evaluation monitoring on the target user. The method solves the problems that the existing method can not carry out targeted monitoring of sleep stages based on effective sleep physiological parameters, affects monitoring rationality and accuracy and can not pertinently propose sleep improvement decisions. The aim of personalized monitoring of different sleep stages is fulfilled, and the effect of improving the scientificity and effectiveness of sleep monitoring is achieved.

Description

A method and system for monitoring physiological parameters of sleep based on intelligent sensing

technical field

The invention relates to the technical field of body monitoring, in particular to a method and system for monitoring sleep physiological parameters based on intelligent sensing.

Background technique

Good sleep is the foundation of human health. Sufficient sleep can quickly restore physical and mental strength. However, with the development of society, people's sleep quality is declining year by year due to various pressures, and more and more patients suffer from sleep disorders. For example, sleep disorders will not only lead to accelerated aging of the body, but also lead to nervous system fatigue leading to neurasthenia, reduced mental work efficiency, lack of energy, memory loss, and even affect the functions of the cardiovascular and cerebrovascular systems, respiratory system, and digestive system. Sleep is an important way to help people quickly recover their physical and mental strength. Automatically monitoring sleep conditions through intelligent monitoring technology, and then accurately and objectively evaluating sleep quality is of great significance for targeted improvement of sleep quality. At present, the intelligent monitoring of human sleep often only focuses on the results of sleep staging, and lacks reasonable utilization and analysis of sleep physiological parameters, such as EEG signals, heart rate signals, respiratory rate and body movement information. For example, when the children of migrant workers monitor and manage the sleep status of their parents at home, they cannot obtain accurate and effective sleep data of their parents, so they cannot accurately analyze the actual sleep status of their parents, resulting in inaccurate health management of their parents. Therefore, effective screening and monitoring of sleep physiological parameters can effectively improve the quality of sleep monitoring and provide a reliable data basis for comprehensive evaluation of sleep quality.

However, when sleep monitoring is performed in the prior art, it is impossible to carry out targeted monitoring of sleep stages based on effective sleep physiological parameters, which affects the scientific rationality, accuracy and effectiveness of sleep monitoring, and ultimately leads to poor sleep monitoring effect and cannot Targeted technical questions for sound sleep improvement decisions.

Contents of the invention

The purpose of the present invention is to provide a sleep physiological parameter monitoring method and system based on intelligent sensing to solve the problem that in the prior art, when sleep monitoring is performed, the targeted monitoring of sleep stages cannot be performed based on effective sleep physiological parameters, and then It affects the scientific rationality, accuracy and effectiveness of sleep monitoring, and ultimately leads to poor sleep monitoring results, and it is impossible to propose reliable sleep improvement decision-making technical problems.

In view of the above problems, the present invention provides a method and system for monitoring sleep physiological parameters based on intelligent sensing.

In a first aspect, the present invention provides a sleep physiological parameter monitoring method based on intelligent sensing, the method is realized by a sleep physiological parameter monitoring system based on intelligent sensing, wherein the method includes: obtaining historical sleep monitoring records , and obtain the first monitoring data based on the historical sleep monitoring records; extract the first sleep monitoring data in the first monitoring data; obtain a preset physiological parameter set, and obtain the first monitoring data based on the first sleep monitoring data Parameter set; monitor the target user based on the first parameter set to obtain sleep parameter information; determine whether the sleep parameter information meets the preset sleep condition, and if so, extract the first formal sleep in the first monitoring data monitoring data, and obtain a second parameter set based on the first official sleep monitoring data; monitor the target user based on the second parameter set, and obtain official sleep parameter information; according to the falling asleep parameter information and the official Sleep parameter information performs sleep quality assessment and monitoring on the target user.

In a second aspect, the present invention also provides a system for monitoring physiological parameters of sleep based on intelligent sensing, which is used to implement the method for monitoring physiological parameters of sleep based on intelligent sensing as described in the first aspect, wherein the system includes: An intelligent acquisition module, which is used to obtain historical sleep monitoring records, and obtains first monitoring data based on the historical sleep monitoring records; an intelligent extraction module, which is used to extract the first sleep monitoring data in the first monitoring data; the second A screening module, which is used to obtain a preset physiological parameter set, and obtain a first parameter set based on the screening of the first sleep monitoring data; a first monitoring module, which is used to monitor the target user based on the first parameter set , to obtain the falling asleep parameter information; the second screening module, which is used to judge whether the falling asleep parameter information meets the preset falling asleep condition, and if so, extract the first formal sleep monitoring data in the first monitoring data, and based on the The first formal sleep monitoring data obtains the second parameter set; the second monitoring module is used to monitor the target user based on the second parameter set to obtain formal sleep parameter information; the intelligent evaluation module is used to obtain the formal sleep parameter information according to the set The sleeping parameter information and the official sleeping parameter information are used to evaluate and monitor the sleep quality of the target user.

One or more technical solutions provided in the present invention have at least the following technical effects or advantages:

By obtaining historical sleep monitoring records, and obtaining first monitoring data based on the historical sleep monitoring records; extracting the first sleep monitoring data in the first monitoring data; obtaining a preset physiological parameter set, and based on the first falling asleep Screening the monitoring data to obtain the first parameter set; monitoring the target user based on the first parameter set to obtain sleep parameter information; judging whether the sleep parameter information meets the preset sleep condition, and if so, extracting the first monitoring data The first formal sleep monitoring data in the system, and obtain a second parameter set based on the first formal sleep monitoring data; monitor the target user based on the second parameter set, and obtain formal sleep parameter information; fall asleep according to the The parameter information and the formal sleep parameter information perform sleep quality evaluation and monitoring on the target user. By obtaining historical sleep monitoring records based on big data, it provides a basis for screening physiological parameters for effective monitoring of each sleep stage, and achieves the technical effect of improving the effectiveness of sleep physiological parameters. Through the calculation and screening of the preset physiological parameter sets, the technical goal of providing parameter guidance for parameter monitoring of different sleep stages is realized, thereby ensuring the comprehensiveness and accuracy of monitoring of each sleep stage, and improving the pertinence of sleep monitoring. Then improve the monitoring efficiency and ensure the technical effect of system performance. Through the intelligent comparison and analysis of the falling asleep parameter information and the preset falling asleep conditions, the time when the user formally falls asleep can be obtained in a timely and accurate manner, and then the physiological parameters of intelligent monitoring can be adjusted to achieve personalized monitoring goals for different sleep stages. The official sleep parameter information is obtained through monitoring, and then combined with the falling asleep parameter information, the intelligent monitoring target of the user's complete sleep is realized, and the data basis and foundation are provided for the intelligent evaluation of the user's sleep quality, and the comprehensiveness and objectivity of sleep quality evaluation are improved. and accuracy of technical effects. It realizes the personalized monitoring goal of different sleep stages, achieves the technical effect of improving the scientificity and effectiveness of sleep monitoring, and then provides objective data basis for targeted improvement of sleep.

The above description is only an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention, it can be implemented according to the contents of the description, and in order to make the above and other purposes, features and advantages of the present invention more obvious and understandable , the specific embodiments of the present invention are enumerated below. It should be understood that the content described in this section is not intended to identify key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will be easily understood from the following description.

Description of drawings

In order to illustrate the present invention or the technical solution in the prior art more clearly, the accompanying drawings that need to be used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings in the following description are only examples In fact, for those of ordinary skill in the art, other drawings can also be obtained according to the provided drawings without creative work.

Fig. 1 is a schematic flow chart of a sleep physiological parameter monitoring method based on intelligent sensing of the present invention;

Fig. 2 is a schematic flow chart of obtaining the first parameter set based on the first analysis result in an intelligent sensing-based sleep physiological parameter monitoring method of the present invention;

3 is a schematic flow diagram of adding the first preset parameter to the first parameter set in an intelligent sensing-based sleep physiological parameter monitoring method according to the present invention;

Fig. 4 is a schematic flow chart of calculating and obtaining the sleep quality evaluation index in an intelligent sensing-based sleep physiological parameter monitoring method of the present invention;

Fig. 5 is a schematic flow diagram of adjusting the sleep quality evaluation index according to the wake-up energy index in an intelligent sensing-based sleep physiological parameter monitoring method of the present invention;

FIG. 6 is a schematic structural diagram of a sleep physiological parameter monitoring system based on intelligent sensing according to the present invention.

Explanation of reference signs:

Intelligent acquisition module 11 , intelligent extraction module 12 , first screening module 13 , first monitoring module 14 , second screening module 15 , second monitoring module 16 , and intelligent evaluation module 17 .

Detailed ways

By providing a sleep physiological parameter monitoring method and system based on intelligent sensing, the present invention solves the problem that sleep monitoring cannot be carried out based on effective sleep physiological parameters in the prior art, thereby affecting sleep monitoring. Scientific rationality and accuracy and effectiveness ultimately lead to poor sleep monitoring results, and it is impossible to propose reliable sleep improvement decision-making technical issues. It realizes the personalized monitoring goal of different sleep stages, achieves the technical effect of improving the scientificity and effectiveness of sleep monitoring, and then provides objective data basis for targeted improvement of sleep.

The acquisition, storage, use, and processing of data in the technical solution of the present invention all comply with the relevant provisions of national laws and regulations.

Below, the technical solutions in the present invention will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments of the present invention. It should be understood that the present invention does not Be limited by the example embodiments described herein. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts fall within the protection scope of the present invention. In addition, it should be noted that, for the convenience of description, only parts related to the present invention are shown in the drawings but not all of them.

Embodiment one

Please refer to accompanying drawing 1, the present invention provides a kind of sleep physiological parameter monitoring method based on intelligent induction, wherein, described method is applied to a kind of sleep physiological parameter monitoring system based on intelligent induction, and described method specifically comprises the following steps:

Step S100: Obtain historical sleep monitoring records, and obtain first monitoring data based on the historical sleep monitoring records;

Specifically, the intelligent sensing-based sleep physiological parameter monitoring method is applied to a sleep physiological parameter monitoring system based on intelligent sensing, which can monitor the user's complete sleep process, thereby realizing complete and accurate sleep monitoring. Target, and provide objective data basis for targeted improvement of sleep. Firstly, based on the big data, the sleep data of all users monitored in history are sorted out, that is, the historical sleep monitoring records are obtained, and then, the complete monitoring record information of any sleep of any user in the historical sleep monitoring records is randomly extracted , that is, as the first monitoring data. Among them, the first monitoring data is used to provide screening data basis and calculation basis for subsequent screening and determination of sleep physiological parameters of each sleep stage, and provide reliable and comprehensive guidance on physiological parameter characteristics for targeted monitoring of each sleep stage, so as to achieve In order to improve the comprehensiveness and effectiveness of sleep monitoring, improve the comprehensive performance of the system at the same time, and provide a basic effect for sleep quality evaluation.

Step S200: Extracting the first sleep monitoring data in the first monitoring data;

Step S300: Acquiring a preset physiological parameter set, and filtering to obtain a first parameter set based on the first sleep monitoring data;

Further, as shown in FIG. 2, step S300 of the present invention includes:

Step S310: Obtain the first preset parameter in the preset physiological parameter set;

Step S320: Obtain first preset parameter information of the first preset parameter in the first sleep monitoring data, wherein the first preset parameter information includes a plurality of parameter monitoring data with time stamps;

Step S330: Generate a first preset parameter graph according to the plurality of parameter monitoring data with time stamps;

Step S340: Analyzing the first preset parameter graph to obtain a first analysis result, and obtaining the first parameter set based on the first analysis result.

Further, as shown in Figure 3, step S340 of the present invention includes:

Step S341: Obtain the first monitoring data at the first time, the second monitoring data at the second time, and the third monitoring data at the third time based on the first preset parameter graph;

Step S342: Wherein, the first time, the second time and the third time have a continuous sequence relationship;

Step S343: judging whether the first monitoring data, the second monitoring data and the third monitoring data conform to a preset correlation;

Step S344: If yes, add the first preset parameter to the first parameter set.

Specifically, the first monitoring data refers to the complete monitoring data of intelligent monitoring of any sleep situation of any user in history. In order to perform targeted monitoring of the user's falling asleep stage based on the data, firstly extract the monitoring data corresponding to all physiological parameters of the user in the falling asleep stage from the first monitoring data, that is, as the first falling asleep monitoring data. Then compare and screen all the physiological parameters in the first sleep monitoring data, and only keep the physiological parameters that have significant changes in the falling asleep stage, that is to say, analyze the parameters in the preset physiological parameter set sequentially, and according to the analysis results Determine whether it should be used as a key physiological parameter to monitor during sleep onset. Wherein, the preset physiological parameter set refers to a comprehensive set of all physiological parameters that may change during the monitoring of human sleep and need to be monitored through comprehensive analysis by relevant experts and technicians, and the preset physiological parameter set pre-stored in the system.

Specifically, any one of the physiological parameters in the preset physiological parameter set is randomly extracted as the first preset parameter, and then the corresponding parameters of the first preset parameter are traversed and extracted from the first sleep monitoring data. The monitoring data is to obtain the first preset parameter information, wherein the first preset parameter information includes a plurality of parameter monitoring data with time stamps. Further, according to the plurality of parameter monitoring data with time stamps, the system automatically generates a first preset parameter graph of monitoring time-monitoring data. Finally, a first analysis result is obtained by analyzing the first preset parameter graph, and the first parameter set is obtained based on the first analysis result. Performing a correlation analysis on the data of the first preset parameter and its sleep state among the plurality of parameter monitoring data with time stamps, so as to screen the parameters whose physiological parameters change significantly under the corresponding sleep stage, as the key monitoring of this stage Parameter index. By obtaining historical sleep monitoring records based on big data, it provides a basis for screening physiological parameters for effective monitoring of each sleep stage, and achieves the technical effect of improving the effectiveness of sleep physiological parameters.

Specifically, first observe the graph of the first preset parameter, and obtain the monitoring results of the first preset parameter at different monitoring times during the falling asleep stage, such as the first monitoring data at the first time and the first monitoring data at the second time. The second monitoring data and the third monitoring data at the third time. Wherein, the first time, the second time and the third time have a continuous sequence relationship, that is, the first monitoring data, the second monitoring data and the third monitoring data are continuous The monitoring value of the first preset parameter monitored three times, and then judge whether the first monitoring data, the second monitoring data and the third monitoring data conform to the preset correlation, wherein, when the first monitoring When the data, the second monitoring data and the third monitoring data conform to the preset correlation, the first preset parameter is added to the first parameter set. Wherein, the preset correlation refers to a positive correlation or a negative correlation. That is to say, when the monitored continuous monitoring result of the first preset parameter presents a specific change trend, it indicates that the user has entered sleep from waking up at this time, that is, is in the stage of falling asleep. Through the calculation and screening of the preset physiological parameter sets, the technical goal of providing parameter guidance for parameter monitoring of different sleep stages is realized, thereby ensuring the comprehensiveness and accuracy of monitoring of each sleep stage, and improving the pertinence of sleep monitoring. Then improve the monitoring efficiency and ensure the technical effect of system performance.

Step S400: Monitor the target user based on the first parameter set to obtain sleep parameter information;

Step S500: Determine whether the falling asleep parameter information meets the preset falling asleep condition, if so, extract the first formal sleep monitoring data from the first monitoring data, and obtain a second parameter set based on the first formal sleep monitoring data ;

Step S600: Monitor the target user based on the second parameter set to obtain formal sleep parameter information;

Specifically, the first parameter set is the key physiological change parameters that the human body will produce when the human body falls asleep, that is, when the human body transitions from waking up to formal sleep. Monitor the target user based on the first parameter set, that is, obtain the falling asleep parameter information of the target user in the falling asleep stage, and then judge whether the falling asleep parameter information meets the preset falling asleep condition, and if so, the system extracts the first monitoring data The first formal sleep monitoring data in , and obtain the second parameter set based on the first formal sleep monitoring data. Similar to the screening and determination scheme of the first parameter set, by analyzing the correlation between each parameter and the actual sleep state in the first formal sleep monitoring data, the physiological parameters that actually affect the formal sleep state are taken as the formal sleep stage The key parameters to monitor, that is, as the second parameter set. Finally, the target user is monitored based on the second parameter set, and formal sleep parameter information of the target user in a formal sleep stage is obtained.

The official sleep parameter information is obtained through monitoring, and then combined with the falling asleep parameter information, the intelligent monitoring target of the user's complete sleep is realized, and the data basis and foundation are provided for the intelligent evaluation of the user's sleep quality, and the comprehensiveness and objectivity of sleep quality evaluation are improved. and accuracy of technical effects. In addition, the data of each stage of the user's sleep is transmitted to the sleep physiological parameter monitoring system, which realizes the goal of the user to log in to the account anytime and anywhere to view the sleep data of each time in his history, and provides objective and specific information for the user to grasp his physical condition in different stages. At the same time, it achieves the technical effect of providing sleep data reference for relatives, friends, private doctors, etc. to monitor the user's sleep in different places and analyze the user's physical state.

Step S700: Evaluate and monitor the sleep quality of the target user according to the falling asleep parameter information and the formal sleep parameter information.

Further, as shown in Figure 4, step S700 of the present invention includes:

Step S710: Obtain a sleep quality evaluation index based on the sleep parameter information;

Further, step S710 of the present invention includes:

Step S711: Randomly extract parameters from the first parameter set, and record them as target parameters;

Step S712: Obtain target parameter information of the target parameter in the falling asleep parameter information;

Step S713: analyzing the target parameter information to obtain the target parameter quality index;

Further, step S713 of the present invention includes:

Step S7131: Based on the target parameter information, acquire initial parameter data at an initial time;

Step S7132: Based on the target parameter information, acquire the last parameter data of the last time;

Step S7133: Calculate the difference between the initial time and the last time to obtain the time span of falling asleep;

Step S7134: Calculate the difference between the initial parameter data and the last parameter data to obtain the parameter change span;

Step S7135: Obtain the change rate of falling asleep of the target parameter according to the falling asleep time span and the parameter changing span;

Step S7136: Perform normalization processing on the rate of change of falling asleep to obtain the target parameter quality index.

Step S714: Obtain the sleep quality evaluation index of the target user based on the target parameter quality index.

Step S720: Obtain a formal sleep quality evaluation index based on the formal sleep parameter information;

Step S730: Calculate the sleep quality evaluation index according to the sleep quality evaluation index and the official sleep quality evaluation index, wherein the calculation formula is as follows:

S=α*S ₁ +β*S ₂

Step S740: Wherein, the S refers to the sleep quality evaluation index, the S1 refers to the sleep quality evaluation index, the α refers to the sleep quality index, and the S2 refers to the official sleep quality evaluation index , the β refers to the official sleep quality coefficient;

Step S750: Wherein, the sleep quality evaluation index is used to characterize the sleep quality of the target user.

Specifically, through the aforementioned collected sleep parameter information and formal sleep parameter information, a full-stage sleep quality assessment and monitoring is performed on the target user. Firstly, the sleep quality evaluation index is obtained based on the falling asleep parameter information, and at the same time, the official sleep quality evaluation index is obtained based on the formal sleep parameter information, and then the sleep quality evaluation is calculated according to the sleep quality evaluation index and the official sleep quality evaluation index Index, wherein, the calculation formula is as follows:

S=α*S ₁ +β*S ₂

Wherein, the S refers to the sleep quality evaluation index, the S1 refers to the sleep quality evaluation index, the α refers to the sleep quality coefficient, the S2 refers to the formal sleep quality evaluation index, and the β refers to the official sleep quality coefficient. Wherein, the sleep quality evaluation index is used to characterize the comprehensive sleep quality of the target user.

Further, when obtaining the sleep quality evaluation index based on the falling asleep parameter information, first arbitrarily extract a parameter in the first parameter set, and record it as the target parameter,

Then traverse to obtain the monitoring data of the target parameter from the falling asleep parameter information, that is, obtain the target parameter information, and then obtain the target parameter quality index by analyzing the target parameter information. Specifically, firstly, among the target parameter information, the target parameter data collected at the initial time, that is, the first time, is used as the initial parameter data, and the last collection, that is, the data collected at the last time is used as the initial parameter data. The data of the target parameter is recorded as the last parameter data. Next, calculate the difference between the initial time and the last time, and use the calculated difference as the time span of falling asleep, and calculate the difference between the initial parameter data and the last parameter data, and use the calculated The difference is taken as the parameter variation span. Next, calculate the ratio between the falling asleep time span and the parameter change span to obtain the falling asleep change rate of the target parameter, and obtain the target parameter quality index by normalizing the falling asleep changing rate . Finally, the sleep quality evaluation index of the target user is obtained based on the target parameter quality index. The official sleep parameter information is obtained through monitoring, and then combined with the falling asleep parameter information, the intelligent monitoring target of the user's complete sleep is realized, and the data basis and foundation are provided for the intelligent evaluation of the user's sleep quality, and the comprehensiveness and objectivity of sleep quality evaluation are improved. and accuracy of technical effects.

Further, as shown in accompanying drawing 5, the present invention also includes the following steps:

Step S761: Obtain the first preset stage and the second preset stage in sequence;

Step S762: Obtain a preset energy assessment plan;

Step S763: Obtain a first energy index of the target user at the first preset stage based on the preset energy assessment scheme;

Step S764: Obtain a second energy index of the target user in the second preset stage based on the preset energy assessment scheme;

Step S765: adding the first energy index and the second energy index to obtain the sleep and wake energy index;

Step S766: Adjust the sleep quality evaluation index according to the sleep energy index.

Specifically, the first preset stage refers to two hours after waking up in the morning, and the second preset stage refers to two hours after having lunch at noon. The preset energy assessment scheme refers to the subjective assessment of the user's energy state in the first preset stage and the second preset stage by the user himself, his surrounding colleagues and family members. For example, the user's energy is divided into three levels, and the user himself, the user's family members, and the user's colleagues make subjective ratings on their energy within two hours after waking up in the morning, such as high energy level, general energy level, and high energy level. Poor class. Next, obtain the first energy index of the target user in the first preset stage based on the preset energy evaluation scheme, and obtain the second energy index of the target user in the second preset stage at the same time, and finally Add the first energy index and the second energy index to obtain the target user's sleep energy index. Finally, the sleep quality evaluation index of the target user is adjusted accordingly according to the sleep energy index.

Through the subjective evaluation of the user's energy state in two special stages, the corresponding user's waking energy index is obtained, and the user's sleep quality evaluation result is adaptively adjusted based on the user's energy state after waking up, so as to improve the user experience. Technical effects of sleep quality assessment accuracy.

In summary, a method for monitoring sleep physiological parameters based on intelligent sensing provided by the present invention has the following technical effects:

By obtaining historical sleep monitoring records, and obtaining first monitoring data based on the historical sleep monitoring records; extracting the first sleep monitoring data in the first monitoring data; obtaining a preset physiological parameter set, and based on the first falling asleep Screening the monitoring data to obtain the first parameter set; monitoring the target user based on the first parameter set to obtain sleep parameter information; judging whether the sleep parameter information meets the preset sleep condition, and if so, extracting the first monitoring data The first formal sleep monitoring data in the system, and obtain a second parameter set based on the first formal sleep monitoring data; monitor the target user based on the second parameter set, and obtain formal sleep parameter information; fall asleep according to the The parameter information and the formal sleep parameter information perform sleep quality evaluation and monitoring on the target user. By obtaining historical sleep monitoring records based on big data, it provides a basis for screening physiological parameters for effective monitoring of each sleep stage, and achieves the technical effect of improving the effectiveness of sleep physiological parameters. Through the calculation and screening of the preset physiological parameter sets, the technical goal of providing parameter guidance for parameter monitoring of different sleep stages is realized, thereby ensuring the comprehensiveness and accuracy of monitoring of each sleep stage, and improving the pertinence of sleep monitoring. Then improve the monitoring efficiency and ensure the technical effect of system performance. Through the intelligent comparison and analysis of the falling asleep parameter information and the preset falling asleep conditions, the time when the user formally falls asleep can be obtained in a timely and accurate manner, and then the physiological parameters of intelligent monitoring can be adjusted to achieve personalized monitoring goals for different sleep stages. The official sleep parameter information is obtained through monitoring, and then combined with the falling asleep parameter information, the intelligent monitoring target of the user's complete sleep is realized, and the data basis and foundation are provided for the intelligent evaluation of the user's sleep quality, and the comprehensiveness and objectivity of sleep quality evaluation are improved. and accuracy of technical effects. It realizes the personalized monitoring goal of different sleep stages, achieves the technical effect of improving the scientificity and effectiveness of sleep monitoring, and then provides objective data basis for targeted improvement of sleep.

Embodiment two

Based on the same inventive concept as the method for monitoring physiological parameters of sleep based on intelligent sensing in the foregoing embodiments, the present invention also provides a monitoring system for physiological parameters of sleep based on intelligent sensing, please refer to accompanying drawing 6, the system includes:

Intelligent acquisition module 11, which is used to acquire historical sleep monitoring records, and obtain the first monitoring data based on the historical sleep monitoring records;

An intelligent extraction module 12, which is used to extract the first sleep monitoring data in the first monitoring data;

A first screening module 13, which is used to obtain a preset physiological parameter set, and obtain a first parameter set based on the first screening of the first sleep monitoring data;

The first monitoring module 14 is configured to monitor the target user based on the first parameter set, and obtain sleep parameter information;

The second screening module 15, which is used to judge whether the falling asleep parameter information meets the preset falling asleep condition, if so, extract the first formal sleep monitoring data in the first monitoring data, and based on the first formal sleep monitoring The data gets the second parameter set;

The second monitoring module 16 is configured to monitor the target user based on the second parameter set to obtain formal sleep parameter information;

An intelligent evaluation module 17, configured to evaluate and monitor the sleep quality of the target user according to the falling asleep parameter information and the formal sleep parameter information.

Further, the first screening module 13 in the system is also used for:

Acquiring a first preset parameter in the set of preset physiological parameters;

Acquiring first preset parameter information of the first preset parameter in the first sleep monitoring data, wherein the first preset parameter information includes a plurality of parameter monitoring data with time stamps;

generating a first preset parameter graph according to the plurality of parameter monitoring data with time stamps;

Analyzing the first preset parameter graph to obtain a first analysis result, and obtaining the first parameter set based on the first analysis result.

Further, the first screening module 13 in the system is also used for:

Based on the first preset parameter graph, the first monitoring data at the first time, the second monitoring data at the second time, and the third monitoring data at the third time are respectively obtained;

Wherein, the first time, the second time and the third time have a continuous sequence relationship;

judging whether the first monitoring data, the second monitoring data, and the third monitoring data conform to a preset correlation;

If yes, adding the first preset parameter to the first parameter set.

Further, the intelligent evaluation module 17 in the system is also used for:

Obtaining a sleep quality evaluation index based on the falling asleep parameter information;

Obtaining a formal sleep quality assessment index based on the formal sleep parameter information;

According to the sleep quality evaluation index and the formal sleep quality evaluation index, the sleep quality evaluation index is calculated, wherein the calculation formula is as follows:

S=α*S ₁ +β*S ₂

Wherein, the S refers to the sleep quality evaluation index, the S1 refers to the sleep quality evaluation index, the α refers to the sleep quality coefficient, the S2 refers to the formal sleep quality evaluation index, and the β is the official sleep quality coefficient;

Wherein, the sleep quality evaluation index is used to characterize the sleep quality of the target user.

Further, the intelligent evaluation module 17 in the system is also used for:

Arbitrarily extracting parameters in the first parameter set, and recording them as target parameters;

acquiring target parameter information of the target parameter in the falling asleep parameter information;

Analyzing the target parameter information to obtain the target parameter quality index;

A sleep quality evaluation index of the target user is obtained based on the target parameter quality index.

Further, the intelligent evaluation module 17 in the system is also used for:

Acquiring initial parameter data at an initial time based on the target parameter information;

Based on the target parameter information, acquire the last parameter data of the last time;

Calculate the difference between the initial time and the last time to obtain the time span of falling asleep;

calculating the difference between the initial parameter data and the last parameter data to obtain a parameter change span;

Obtaining the rate of change of falling asleep of the target parameter according to the time span of falling asleep and the span of changing the parameter;

The rate of change of falling asleep is normalized to obtain the target parameter quality index.

Further, the intelligent evaluation module 17 in the system is also used for:

Obtain the first preset stage and the second preset stage in turn;

Obtain a preset energy assessment plan;

Obtaining a first energy index of the target user at the first preset stage based on the preset energy assessment scheme;

Obtaining a second energy index of the target user at the second preset stage based on the preset energy assessment scheme;

adding the first energy index and the second energy index to obtain the sleep and wake energy index;

The sleep quality evaluation index is adjusted according to the wake-up energy index.

Each embodiment in this description is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. A method for monitoring physiological parameters of sleep based on intelligent sensing in the first embodiment of Figure 1 The specific example is also applicable to a sleep physiological parameter monitoring system based on intelligent sensing in this embodiment. Through the foregoing detailed description of a sleep physiological parameter monitoring method based on smart sensing, those skilled in the art can clearly understand that this embodiment The example is a sleep physiological parameter monitoring system based on intelligent sensing, so for the sake of brevity of the description, it will not be described in detail here. As for the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and for the related part, please refer to the description of the method part.

The above description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention will not be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention belong to the scope of the present invention and its equivalent technology, the present invention also intends to include these modifications and variations.

Claims (8)

1. The sleep physiological parameter monitoring method based on intelligent sensing is characterized by comprising the following steps of:

acquiring a historical sleep monitoring record, and acquiring first monitoring data based on the historical sleep monitoring record;

extracting first sleep-entering monitoring data in the first monitoring data;

acquiring a preset physiological parameter set, and screening to obtain a first parameter set based on the first sleep monitoring data;

monitoring a target user based on the first parameter set to obtain sleeping parameter information;

judging whether the sleep parameter information accords with a preset sleep condition, if so, extracting first formal sleep monitoring data in the first monitoring data, and obtaining a second parameter set based on the first formal sleep monitoring data;

monitoring the target user based on the second parameter set to obtain formal sleep parameter information;

and carrying out sleep quality evaluation monitoring on the target user according to the sleep-entering parameter information and the formal sleep parameter information.

2. The sleep physiological parameter monitoring method according to claim 1, wherein the acquiring a preset physiological parameter set and screening to obtain a first parameter set based on the first sleep-in monitoring data comprises:

acquiring a first preset parameter in the preset physiological parameter set;

acquiring first preset parameter information of the first preset parameter in the first sleep-in monitoring data, wherein the first preset parameter information comprises a plurality of parameter monitoring data with time identifiers;

generating a first preset parameter curve graph according to the plurality of parameter monitoring data with the time marks;

analyzing the first preset parameter graph to obtain a first analysis result, and obtaining the first parameter set based on the first analysis result.

3. The method of claim 2, wherein analyzing the first preset parameter profile to obtain a first analysis result and obtaining the first parameter set based on the first analysis result comprises:

based on the first preset parameter graph, respectively obtaining first monitoring data of a first time, second monitoring data of a second time and third monitoring data of a third time;

wherein the first time, the second time, and the third time have a sequential order relationship;

judging whether the first monitoring data, the second monitoring data and the third monitoring data accord with a preset correlation;

if yes, adding the first preset parameters to the first parameter set.

4. The sleep physiological parameter monitoring method according to claim 1, wherein the sleep quality evaluation monitoring of the target user according to the sleep-in parameter information and the formal sleep parameter information comprises:

obtaining a sleep quality assessment index based on the sleep parameter information;

obtaining a formal sleep quality assessment index based on the formal sleep parameter information;

according to the sleep quality assessment index and the formal sleep quality assessment index, calculating to obtain a sleep quality assessment index, wherein a calculation formula is as follows:

S＝α*S ₁ +β*S ₂

the system comprises a sleep quality evaluation index, an alpha and a beta, wherein S is the sleep quality evaluation index, S1 is the sleep quality evaluation index, alpha is the sleep quality coefficient, S2 is the formal sleep quality evaluation index, and beta is the positive sleep quality coefficient;

wherein the sleep quality assessment index is used to characterize the sleep quality of the target user.

5. The sleep physiological parameter monitoring method according to claim 4, wherein the deriving a sleep quality assessment index based on the sleep onset parameter information comprises:

randomly extracting parameters in the first parameter set and recording the parameters as target parameters;

acquiring target parameter information of the target parameters in the sleep-entering parameter information;

analyzing the target parameter information to obtain a target parameter quality index;

and obtaining the sleep quality assessment index of the target user based on the target parameter quality index.

6. The method for monitoring sleep physiological parameters according to claim 5, wherein said analyzing the target parameter information to obtain a target parameter quality index comprises:

acquiring initial parameter data of initial time based on the target parameter information;

acquiring last bit parameter data of last bit time based on the target parameter information;

calculating the difference value between the initial time and the final time to obtain a sleep time span;

calculating the difference value of the initial parameter data and the final parameter data to obtain a parameter change span;

obtaining the sleep-in change rate of the target parameter according to the sleep-in time span and the parameter change span;

and normalizing the sleep-in change rate to obtain the quality index of the target parameter.

7. The sleep physiological parameter monitoring method according to claim 4, further comprising:

sequentially obtaining a first preset stage and a second preset stage;

acquiring a preset energy assessment scheme;

obtaining a first energy index of the target user in the first preset stage based on the preset energy evaluation scheme;

obtaining a second energy index of the target user in the second preset stage based on the preset energy evaluation scheme;

adding the first energy index and the second energy index to obtain a wake energy index;

and adjusting the sleep quality assessment index according to the wake-up energy index.

8. Sleep physiological parameter monitoring system based on intelligence response, characterized in that, sleep physiological parameter monitoring system includes:

the intelligent acquisition module is used for acquiring a history sleep monitoring record and acquiring first monitoring data based on the history sleep monitoring record;

the intelligent extraction module is used for extracting first sleep-entering monitoring data in the first monitoring data;

the first screening module is used for acquiring a preset physiological parameter set and screening to obtain a first parameter set based on the first sleep monitoring data;

the first monitoring module is used for monitoring the target user based on the first parameter set to obtain sleeping parameter information;

the second screening module is used for judging whether the sleep parameter information accords with a preset sleep condition, if so, extracting first formal sleep monitoring data in the first monitoring data, and obtaining a second parameter set based on the first formal sleep monitoring data;

the second monitoring module is used for monitoring the target user based on the second parameter set to obtain formal sleep parameter information;

and the intelligent evaluation module is used for evaluating and monitoring the sleep quality of the target user according to the sleep-entering parameter information and the formal sleep parameter information.

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