Disclosure of Invention
The invention aims to provide an electric bed sleep-aiding control system based on big data, which solves the problems in the background technology.
In order to solve the technical problems, the technical scheme is that the electric bed sleep-aiding control system based on big data comprises a sleep-aiding control scheme preset module, a sleep monitoring analysis module, a sleep-aiding scheme correction module, a sleep state evaluation module and a database.
The sleep-aiding control scheme preset module is used for extracting information parameters, sleep state parameters and electric bed control parameters of each user from a database, calculating sleep state coincidence coefficients of each user in a sleep monitoring period of each user based on the sleep state parameters of each user, generating sleep-aiding control schemes of each user, acquiring information parameters of each user, and matching initial sleep-aiding control schemes of the users from the sleep-aiding control schemes of the users.
The sleep monitoring analysis module is used for acquiring sleep parameters in the sleep monitoring period of the target user and calculating the sleep state coincidence coefficient in the sleep monitoring period of the target user based on the sleep parameters in the sleep monitoring period of the target user.
The sleep-aiding scheme correction module calculates the initial sleep-aiding control scheme coincidence coefficient based on the sleep state coincidence coefficient of the target user and the sleep state coincidence coefficient of each user in the sleep monitoring period corresponding to the initial sleep-aiding control scheme, and selects the sleep control scheme of the corresponding type user of the target user from the database again to generate a corrected sleep-aiding control scheme.
The sleep state evaluation module is used for acquiring each sleep parameter in the sleep monitoring period of the target user after correction based on the corrected sleep control scheme, calculating the sleep state coincidence coefficient in the sleep monitoring period of the target user after correction, and evaluating the sleep state coincidence level in the sleep monitoring period of the target user after correction.
The sleep state coincidence coefficient in each user sleep monitoring period is calculated, and the specific analysis method comprises the steps that each parameter of the sleep state comprises respiratory rate, heart rate, sleep duration and body movement times.
Respiratory rate at each acquisition point within each user sleep monitoring period based on historic extracted from a databaseHeart rateSleep duration in history of sleep monitoring periods of each userSum of body movement timesWherein,The number of each user representing the history is displayed,Representing the total number of historical users,,The number of each acquisition point in the sleep monitoring period is represented,Representing the total number of acquisition points in the sleep monitoring period.
By the formula: Calculating to obtain coincidence judgment value of respiratory rate of each acquisition point in sleep monitoring period of each userWhereinRepresenting the standard respiratory rate within the user sleep monitoring period extracted from the database.
Analyzing the heart rate of each sampling point in the sleep monitoring period of each user according to the operation method of the coincidence judgment value of the respiratory rate of each sampling point in the monitoring period to obtain the coincidence judgment value of the heart rate of each sampling point in the sleep monitoring period of each user。
By the formula: Calculating to obtain the sleep state coincidence coefficient of each user in the sleep monitoring periodWhereinAn influence factor representing a unit sleep duration extracted from the database,An influence factor representing the number of unit body movements extracted from the database,Representing natural constants.
Specifically, a sleep-aiding control scheme for each type of user is generated, wherein the specific analysis method comprises the steps of conforming the sleep state in the sleep monitoring period of each user to the coefficient based on historyIf (if)Then determine the firstSleep state is good during a bit user sleep monitoring period, whereinA decision threshold representing the sleep state extracted from the database.
If it isThen determine the firstThe sleep state of the user in the sleep monitoring period is disqualified.
According to the firstThe method for judging the sleep state in the sleep monitoring period of the user judges the sleep state coincidence coefficient of each user in the sleep monitoring period of the history, and obtains each user with good sleep state in the sleep monitoring period of the history.
And extracting sleep control schemes of all users with good sleep states in a historical sleep monitoring period and parameters of information from a database, wherein the parameters of the information comprise gender and age.
Firstly, dividing according to the sexes of all users with good sleep states in a historical sleep monitoring period to obtain all users with good sleep states in the historical sleep monitoring period after sex division, and dividing all users with good sleep states in the historical sleep monitoring period according to age intervals extracted from a database to obtain all types of users with good sleep states in the historical sleep monitoring period.
Based on the sleep state coincidence coefficients of all types of users with good sleep states in the historical sleep monitoring period, the sleep environment parameters and the electric bed control parameters in the historical sleep monitoring period corresponding to the maximum sleep state coincidence coefficients of all types of users are obtained through screening, and the sleep environment parameters and the electric bed control parameters in the historical sleep monitoring period corresponding to the maximum sleep state coincidence coefficients of all types of users are combined to form a sleep-aiding control scheme of all types of users.
The parameters of the sleeping environment comprise the ambient temperature, the ambient humidity and the frequency of the sleep-aiding audio.
The parameters of the electric bed control include back angle, leg angle and overall inclination angle.
The specific analysis method comprises the steps of obtaining information parameters of a target user from a database, and matching the information parameters from proper sleep control methods of various types of users based on the gender and age of the target user to obtain the initial sleep control scheme of the target user.
The method comprises obtaining sleep parameters of target user in sleep monitoring period under initial sleep control scheme, including respiratory rate of target user at each monitoring point in sleep monitoring periodHeart rateSleep duration in target user sleep monitoring periodSum of body movement timesWherein,A number representing each monitoring point in the sleep monitoring period,Representing the total number of monitoring points within the sleep monitoring period.
By the formula: Calculating to obtain the coincidence judgment value of the respiratory frequency of each monitoring point in the sleep monitoring period of the target user。
Analyzing the heart rate of each monitoring point in the sleep monitoring period of the target user according to the operation method of the coincidence judgment value of the respiratory rate of each monitoring point in the sleep monitoring period of the target user to obtain the coincidence judgment value of the heart rate of each monitoring point in the sleep monitoring period of the target user。
By the formula: calculating to obtain the sleep state coincidence coefficient of the target user in the sleep monitoring period. Extracting the sleep state coincidence coefficient of each user in the sleep monitoring period corresponding to the initial sleep control scheme of the target user from a database, carrying out average processing on the sleep state coincidence coefficient of each user in the sleep monitoring period corresponding to the initial sleep control scheme of the target user, and taking the average result as the standard sleep state coincidence coefficient in the monitoring period of the target user;
Sleep state coincidence coefficient in sleep monitoring period based on target userBy the formula: Calculating to obtain initial sleep control scheme coincidence coefficient of target user。
Specifically, a corrected sleep control scheme is generated, and the specific analysis method comprises the following steps of conforming the initial sleep control scheme based on a target user to coefficientsIf (if)And if the initial sleep control scheme accords with the first interval of the coefficient, judging that the initial sleep control scheme accords with the high level of the target user.
If it isAnd if the initial sleep control scheme extracted from the database accords with the second interval of the coefficient, judging that the initial sleep control scheme of the target user accords with the low level, and implementing the response measure of the initial sleep control scheme of the target user accords with the low level.
The initial sleep-aiding control scheme of the target user accords with response measures with low coincidence level, specifically, the sleep state coincidence coefficients of the historical users of the corresponding types of the information parameters of the target user are extracted from a database, the sleep environment parameters and the electric bed control parameters in the historical sleep monitoring period corresponding to the second largest sleep state coincidence coefficients are selected, and the corrected sleep-aiding control scheme is formed.
The method comprises the steps of obtaining each parameter of sleep of a target user in a sleep monitoring period under a modified sleep control scheme, and obtaining the sleep state coincidence coefficient of the target user in the sleep monitoring period under the modified sleep control scheme according to the operation method of the sleep state coincidence coefficient of the target user in the sleep monitoring period under an initial sleep control scheme。
Specifically, the sleep state coincidence level in the sleep monitoring period of the target user after correction is evaluated, and the specific analysis method comprises the following steps of based on the sleep state coincidence coefficient of the target user in the sleep monitoring period under the sleep control scheme after correctionBy the formula: the sleep state coincidence coefficient of the target user after correction is obtained through operation。
If it isAnd if the sleep state of the corrected target user extracted from the database accords with the first interval, judging that the sleep state accords with the high level.
If it isAnd if the sleep state of the corrected target user extracted from the database accords with the second interval, judging that the sleep state compliance level of the corrected target user is low.
If the corrected sleep state coincidence level of the target user is low coincidence, sequentially selecting each parameter of the sleep environment and each parameter of the electric bed control in the history sleep monitoring period corresponding to the sleep state coincidence coefficient according to the sequence from large to small, reconstructing a corrected sleep control scheme, and evaluating the corrected sleep state coincidence level of the target user again until the corrected sleep state coincidence level of the target user is high coincidence.
Compared with the prior art, the invention has the advantages that firstly, the technology of big data analysis is adopted, the sleep parameters and the information parameters in the sleep monitoring period of each user are analyzed, the sleep control scheme of each type of user is obtained by screening, the target user can be conveniently and rapidly matched with the initial sleep control scheme of the target user according to the information parameters, the use technical threshold of the electric bed is reduced, and the use convenience of the sleep control scheme of the electric bed is improved.
2. The invention continuously monitors the sleep parameters in the sleep monitoring period of the target user, and is convenient for finding the sleep state in the sleep monitoring period of the target user in time, so that the sleep-assisting control scheme of the electric bed of the target user is corrected in time, the self-learning capacity of the electric bed sleep-assisting control system is improved, and the reliability of the electric bed sleep-assisting control system is realized.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the invention provides an electric bed sleep-aiding control system based on big data, which comprises a sleep-aiding control scheme presetting module, a sleep monitoring analysis module, a sleep-aiding scheme correcting module, a sleep state evaluating module and a database.
The sleep-aiding control scheme preset module is used for extracting information parameters, sleep state parameters and electric bed control parameters of each user from a database, calculating sleep state coincidence coefficients of each user in a sleep monitoring period of each user based on the sleep state parameters of each user, generating sleep-aiding control schemes of each user, acquiring information parameters of each user, and matching initial sleep-aiding control schemes of the users from the sleep-aiding control schemes of the users.
The sleep monitoring analysis module is used for acquiring sleep parameters in the sleep monitoring period of the target user and calculating the sleep state coincidence coefficient in the sleep monitoring period of the target user based on the sleep parameters in the sleep monitoring period of the target user.
The sleep-aiding scheme correction module calculates the initial sleep-aiding control scheme coincidence coefficient based on the sleep state coincidence coefficient of the target user and the sleep state coincidence coefficient of each user in the sleep monitoring period corresponding to the initial sleep-aiding control scheme, and selects the sleep control scheme of the corresponding type user of the target user from the database again to generate a corrected sleep-aiding control scheme.
The sleep state evaluation module is used for acquiring each sleep parameter in the sleep monitoring period of the target user after correction based on the corrected sleep control scheme, calculating the sleep state coincidence coefficient in the sleep monitoring period of the target user after correction, and evaluating the sleep state coincidence level in the sleep monitoring period of the target user after correction.
The database is used for storing the respiratory rate and the heart rate of each acquisition point in each sleep monitoring period of each user, storing the sleep duration and the body movement times in each sleep monitoring period of each user, storing the standard respiratory rate in the sleep monitoring period of each user, storing the influence factors of the unit sleep duration and the unit body movement times, storing the sleep state judgment threshold, storing the initial sleep control scheme to accord with each interval of the coefficient, and storing the sleep state of the corrected target user to accord with each interval.
It should be noted that, in a specific embodiment, the sleep-aiding control scheme preset module is connected with the sleep monitoring analysis module, the sleep monitoring analysis module is connected with the sleep-aiding scheme correction module, the sleep-aiding scheme correction module is connected with the sleep state evaluation module, and the database is connected with the sleep-aiding control scheme preset module, the sleep monitoring analysis module, the sleep-aiding scheme correction module and the sleep state evaluation module.
In the specific embodiment of the invention, the sleep state coincidence coefficient of each user in the sleep monitoring period of the operation history is calculated, and the specific analysis method comprises the steps of calculating each parameter of the sleep state including the respiratory rate, the heart rate, the sleep duration and the body movement times.
Respiratory rate at each acquisition point within each user sleep monitoring period based on historic extracted from a databaseHeart rateSleep duration in history of sleep monitoring periods of each userSum of body movement timesWherein,The number of each user representing the history is displayed,Representing the total number of historical users,,The number of each acquisition point in the sleep monitoring period is represented,Representing the total number of acquisition points in the sleep monitoring period.
By the formula: Calculating to obtain coincidence judgment value of respiratory rate of each acquisition point in sleep monitoring period of each userWhereinRepresenting the standard respiratory rate within the user sleep monitoring period extracted from the database.
Analyzing the heart rate of each sampling point in the sleep monitoring period of each user according to the operation method of the coincidence judgment value of the respiratory rate of each sampling point in the monitoring period to obtain the coincidence judgment value of the heart rate of each sampling point in the sleep monitoring period of each user。
The method comprises the steps of firstly adopting a low-pass filter (such as Butterworth) to eliminate heart rate noise, removing extreme abnormal values, dividing heart rate data according to sleep stages (such as deep sleep, shallow sleep and REM), adapting heart rate standards of different stages, secondly determining a normal heart rate range through a general standard method and a personalized baseline method, calculating average value and standard deviation of sleep heart rates of each user in the history by taking the personalized baseline method as an example, determining the heart rate range through the average value and the standard deviation, finally calculating coincidence judgment values of the heart rates, and carrying out point-by-point judgment according to a calculation formula of coincidence judgment values of the respiratory frequencies.
By the formula: Calculating to obtain the sleep state coincidence coefficient of each user in the sleep monitoring periodWhereinAn influence factor representing a unit sleep duration extracted from the database,An influence factor representing the number of unit body movements extracted from the database,Representing natural constants.
In the specific embodiment of the invention, a sleep-aiding control scheme of each type of user is generated, and the specific analysis method comprises the following steps of conforming the sleep state to the coefficient in the sleep monitoring period of each user based on historyIf (if)Then determine the firstSleep state is good during a bit user sleep monitoring period, whereinA decision threshold representing the sleep state extracted from the database.
If it isThen determine the firstThe sleep state of the user in the sleep monitoring period is disqualified.
In a specific embodiment, the sleep state judgment threshold is comprehensively analyzed by a technician according to the sleep state coincidence coefficient in the sleep monitoring period of each user and the actual sleep experience of each user, is preset manually, and is stored in the database.
According to the firstThe method for judging the sleep state in the sleep monitoring period of the user judges the sleep state coincidence coefficient of each user in the sleep monitoring period of the history, and obtains each user with good sleep state in the sleep monitoring period of the history.
And extracting sleep control schemes of all users with good sleep states in a historical sleep monitoring period and parameters of information from a database, wherein the parameters of the information comprise gender and age.
Firstly, dividing according to the sexes of all users with good sleep states in a historical sleep monitoring period to obtain all users with good sleep states in the historical sleep monitoring period after sex division, and dividing all users with good sleep states in the historical sleep monitoring period according to age intervals extracted from a database to obtain all types of users with good sleep states in the historical sleep monitoring period.
In a specific embodiment, the age intervals are set according to a certain span, and stored in a database, for example, the age intervals are set according to a span of 5, so as to obtain the age intervals:。
Based on the sleep state coincidence coefficients of all types of users with good sleep states in the historical sleep monitoring period, the sleep environment parameters and the electric bed control parameters in the historical sleep monitoring period corresponding to the maximum sleep state coincidence coefficients of all types of users are obtained through screening, and the sleep environment parameters and the electric bed control parameters in the historical sleep monitoring period corresponding to the maximum sleep state coincidence coefficients of all types of users are combined to form a sleep-aiding control scheme of all types of users.
The parameters of the sleeping environment comprise the ambient temperature, the ambient humidity and the frequency of the sleep-aiding audio.
In a specific embodiment, the temperature sensor collects the ambient temperature, the humidity sensor collects the ambient humidity, and the audio sensor collects the frequency of the sleep-aiding audio.
The parameters of the electric bed control include back angle, leg angle and overall inclination angle.
In the specific embodiment of the invention, the initial sleep control scheme of the target user is matched, and the specific analysis method comprises the steps of acquiring information parameters of the target user from a database, and matching from the proper sleep control methods of various types of users based on the gender and age of the target user to obtain the initial sleep control scheme of the target user.
According to the invention, a big data analysis technology is adopted to analyze each sleep parameter and each information parameter in the sleep monitoring period of each user in history, and the sleep control scheme of each type of user is obtained by screening, so that the target user can be matched with the initial sleep control scheme of the target user according to each information parameter, the use technical threshold of the electric bed is reduced, and the use convenience of the sleep control scheme of the electric bed is improved.
In the specific embodiment of the invention, the sleep state coincidence coefficient of the target user in the sleep monitoring period is calculated, and the specific analysis method comprises the steps of obtaining each sleep parameter of the target user in the sleep monitoring period under the initial sleep control scheme, including the respiratory rate of each monitoring point of the target user in the sleep monitoring periodHeart rateSleep duration in target user sleep monitoring periodSum of body movement timesWhereinRepresentingThe number of each monitoring point in the sleep monitoring period,Representing the total number of monitoring points within the sleep monitoring period.
In a specific embodiment, the target user wears the intelligent means in the sleep process, the breathing frequency in the sleep monitoring period of the target user is collected through the breathing frequency sensor integrated by the intelligent bracelet, the heart rate in the sleep monitoring period of the target user is collected through the heart rate sensor, and the sleep duration and the body movement times in the sleep monitoring period of the target user are collected through the intelligent bracelet.
By the formula: Calculating to obtain the coincidence judgment value of the respiratory frequency of each monitoring point in the sleep monitoring period of the target user。
Specifically, the coincidence judgment value of the heart rate of each monitoring point in the sleep monitoring period of the target user is consistent with the coincidence judgment value of the heart rate of each acquisition point in the sleep monitoring period of the history user, and redundant description is omitted here.
Analyzing the heart rate of each monitoring point in the sleep monitoring period of the target user according to the operation method of the coincidence judgment value of the respiratory rate of each monitoring point in the sleep monitoring period of the target user to obtain the coincidence judgment value of the heart rate of each monitoring point in the sleep monitoring period of the target user。
By the formula: calculating to obtain the sleep state coincidence coefficient of the target user in the sleep monitoring period。
Further, the sleep state coincidence coefficient is obtained by integrating the actual sleep data (respiratory rate, heart rate, sleep duration and body movement times) of the target user and distributing the influence factors of the corresponding items, wherein the sleep state coincidence coefficient is a normalized comprehensive score.
In the specific embodiment of the invention, the method for analyzing the initial sleep-aiding control scheme coincidence coefficient comprises the steps of extracting the sleep state coincidence coefficient of each user in the sleep monitoring period of the history corresponding to the initial sleep-aiding control scheme of the target user from a database, carrying out average processing on the sleep state coincidence coefficient of each user in the sleep monitoring period of the history corresponding to the initial sleep-aiding control scheme of the target user, and taking the average result as the standard sleep state coincidence coefficient in the monitoring period of the target user;
Sleep state coincidence coefficient in sleep monitoring period based on target userBy the formula: Calculating to obtain initial sleep control scheme coincidence coefficient of target user。
In the specific embodiment of the invention, a corrected sleep control scheme is generated, and the specific analysis method comprises the following steps that the initial sleep control scheme based on the target user accords with the coefficientIf (if)And if the initial sleep control scheme accords with the first interval of the coefficient, judging that the initial sleep control scheme accords with the high level of the target user.
If it isAnd if the initial sleep control scheme extracted from the database accords with the second interval of the coefficient, judging that the initial sleep control scheme of the target user accords with the low level, and implementing the response measure of the initial sleep control scheme of the target user accords with the low level.
In a specific embodiment, the initial sleep-aiding control scheme accords with each interval of the coefficient, and the technician performs comprehensive analysis according to the coefficient and the actual sleep experience according to the initial sleep-aiding control scheme of each user, and performs artificial preset and stores the result in the database.
The initial sleep-aiding control scheme of the target user accords with response measures with low coincidence level, specifically, the sleep state coincidence coefficients of the historical users of the corresponding types of the information parameters of the target user are extracted from a database, the sleep environment parameters and the electric bed control parameters in the historical sleep monitoring period corresponding to the second largest sleep state coincidence coefficients are selected, and the corrected sleep-aiding control scheme is formed.
In the specific embodiment of the invention, the sleep state coincidence coefficient of the target user in the sleep monitoring period after correction is calculated, and the specific analysis method comprises the steps of obtaining each sleep parameter of the target user in the sleep monitoring period under the sleep control scheme after correction, and obtaining the sleep state coincidence coefficient of the target user in the sleep monitoring period under the sleep control scheme after correction according to the calculation method of the sleep state coincidence coefficient of the target user in the sleep monitoring period under the initial sleep control scheme。
In a specific embodiment of the invention, the sleep state coincidence level in the sleep monitoring period of the target user after correction is evaluated, and the specific analysis method comprises the following steps:
sleep state coincidence coefficient in sleep monitoring period based on target user under modified sleep control schemeBy the formula: the sleep state coincidence coefficient of the target user after correction is obtained through operation。
If it isAnd if the sleep state of the corrected target user extracted from the database accords with the first interval, judging that the sleep state accords with the high level.
If it isAnd if the sleep state of the corrected target user extracted from the database accords with the second interval, judging that the sleep state compliance level of the corrected target user is low.
In a specific embodiment, the sleep state of the target user after correction accords with each interval, and the technician performs comprehensive analysis according to the sleep state coincidence coefficient of the target user after each correction according to the history and the actual sleep experience, and performs manual preset storage in the database.
If the corrected sleep state coincidence level of the target user is low coincidence, sequentially selecting each parameter of the sleep environment and each parameter of the electric bed control in the history sleep monitoring period corresponding to the sleep state coincidence coefficient according to the sequence from large to small, reconstructing a corrected sleep control scheme, and evaluating the corrected sleep state coincidence level of the target user again until the corrected sleep state coincidence level of the target user is high coincidence.
The invention continuously monitors the sleep parameters in the sleep monitoring period of the target user, and is convenient for finding the sleep state in the sleep monitoring period of the target user in time, so that the sleep-assisting control scheme of the electric bed of the target user is corrected in time, the self-learning capacity of the electric bed sleep-assisting control system is improved, and the reliability of the electric bed sleep-assisting control system is realized.
The foregoing is merely illustrative and explanatory of the principles of this invention, as various modifications and additions may be made to the specific embodiments described, or similar arrangements may be substituted by those skilled in the art, without departing from the principles of this invention or beyond the scope of this invention as defined in the claims.