CN113205887A - Big data and artificial intelligence based intelligent aged-care user full-period tracking analysis method, system and storage medium - Google Patents

Big data and artificial intelligence based intelligent aged-care user full-period tracking analysis method, system and storage medium Download PDF

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CN113205887A
CN113205887A CN202110591898.4A CN202110591898A CN113205887A CN 113205887 A CN113205887 A CN 113205887A CN 202110591898 A CN202110591898 A CN 202110591898A CN 113205887 A CN113205887 A CN 113205887A
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饶雪瑜
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Abstract

The invention discloses a method, a system and a storage medium for intelligent aged-care user full-period tracking analysis based on big data and artificial intelligence, which classify all aged-care users in an aged-care institution according to the corresponding self-care ability types to obtain self-care aged-care users and non-self-care aged-care users, and respectively acquire the body health parameters of the respective self-care aged-care users and the non-self-care aged-care users in the set monitoring period, thereby evaluating the body health coefficients of the respective self-care aged-care users and the respective non-self-care aged-care users in the set monitoring period, realizing the full-period tracking analysis of the body health of the aged-care users of the aged-care institution, deepening and customizing the aged-care service function of the aged-care users of the aged-care institution, greatly overcoming the defects that the aged-care service of the aged-care institution is rough and the degree is insufficient at present, the endowment experience of endowment users is improved, and the endowment service level of an endowment mechanism is further improved.

Description

Big data and artificial intelligence based intelligent aged-care user full-period tracking analysis method, system and storage medium
Technical Field
The invention belongs to the technical field of endowment analysis, and particularly relates to a method and a system for intelligent endowment user full-period tracking analysis based on big data and artificial intelligence and a storage medium.
Background
In recent years, with the aggravation of the aging degree of China and the improvement of the living standard of people, the traditional endowment mode and the endowment concept of China are changed to social endowment, and the requirement on an endowment service organization is rapidly increased, so that great challenges are brought to the quantity and the service quality of the traditional endowment organization.
In order to meet the quantitative requirements of the endowment users on the endowment institutions, a large number of endowment institutions for office, civil and social organizations emerge, and the quantitative requirements of the endowment users on the endowment service institutions can be fully met. But most endowment institutions are not high to endowment user's service level at present, this concrete embodiment is in that the endowment service depth degree that present endowment institution provided endowment user is not enough, mostly stop in the basic life service to endowment user, do not track the monitoring to endowment user's health status according to endowment user's daily basic life cycle, lead to the health status that can't in time learn all endowment users, and then be difficult to the pertinence maintenance scheme of giving, make endowment institution endowment service comparatively extensive, the careful degree is not enough, the endowment experience of endowment user has been reduced.
Disclosure of Invention
In order to overcome at least the defects in the prior art, the invention provides a full-period tracking analysis method, a system and a storage medium for intelligent aged-care users based on big data and artificial intelligence.
The purpose of the invention can be realized by the following technical scheme:
in a first aspect, the intelligent aged-care user full-period tracking analysis method based on big data and artificial intelligence comprises the following steps:
s1, evaluating the self-care ability of the aged-care user: the physical self-care ability evaluation module is used for evaluating the physical self-care ability of the aged-care users who live in the aged-care institution during the live in, and determining the types of the physical self-care ability according to the evaluation result to obtain the types of the physical self-care ability corresponding to the aged-care users;
s2, classifying the aged-care users: classifying the aged users corresponding to the same body self-care ability type through an aged user classification module to obtain aged users corresponding to the self-care ability type and aged users corresponding to the non self-care ability type, wherein the aged users corresponding to the self-care ability type are marked as self-care aged users, the aged users corresponding to the non self-care ability type are marked as non-self-care aged users, at the moment, the aged users are numbered respectively as 1,2, a.
S3, evaluating the body health coefficient of the self-care aged-care user: collecting three-meal food intake, physical quality parameters, sleeping time and outdoor area activity time corresponding to each physical elderly user every day in a set monitoring period according to the physical health analysis module of the self-care elderly users, and evaluating the physical health coefficients corresponding to each physical elderly user in the set monitoring period according to the three-meal food intake, the physical quality parameters, the sleeping time and the outdoor area activity time;
s4, evaluating the body health coefficient of the user without self-care for the aged: collecting an on-time coefficient of feeding time of a nursing staff corresponding to each non-self-care elderly user and a physical quality parameter and a sleeping time length corresponding to each day according to the body health analysis module of the non-self-care elderly user in a set monitoring period, and evaluating the body health coefficient corresponding to each non-self-care elderly user in the set monitoring period according to the on-time coefficient;
s5, acquiring the body health grade of the aged-care user: comparing the body health coefficient corresponding to each self-care elderly user in the set monitoring period with the body health coefficient range corresponding to various body health grades of the self-care elderly user in the elderly health database through the analysis server to obtain the body health grade corresponding to each self-care elderly user in the set monitoring period, and comparing the body health coefficient corresponding to each non-self-care elderly user in the set monitoring period with the body health coefficient range corresponding to various body health grades of the non-self-care elderly user in the elderly health database to obtain the body health grade corresponding to each non-self-care elderly user in the set monitoring period;
s6, classifying the physical health grade of the aged-care user: comparing the body health grade corresponding to each physical endowment user in a set monitoring period with the body health grade corresponding to each non-self-care endowment user in the set monitoring period through an analysis server, so as to collect the self-care endowment users corresponding to the same body health grade and the non-self-care endowment users corresponding to the same body health grade, and obtain a self-care endowment user set corresponding to various body health grades and a non-self-care endowment user set corresponding to various body health grades;
s7, displaying the body health grade of the aged-care user: sequencing the self-care elderly care user sets corresponding to various body health levels and the non-self-care elderly care user sets corresponding to various body health levels from large to small according to the body health levels through the display terminal, obtaining sequencing results of the self-care elderly care user sets corresponding to various body health levels and sequencing results of the non-self-care elderly care user sets corresponding to various body health levels, and displaying the sequencing results.
According to a preferred embodiment of the first aspect of the present invention, the method for acquiring the body quality parameters corresponding to the respective physical elderly care users and the respective non-self care elderly care users is to wear an intelligent wearable terminal on the respective physical elderly care users and the respective non-self care elderly care users, wherein the intelligent wearable terminal is internally provided with a body quality parameter acquisition unit, a GPS positioning instrument and a camera, the body quality parameter acquisition unit comprises a thermistor, a photoelectric sensor and a pressure measuring instrument, wherein the thermistor is used for acquiring the body temperature of the elderly care users, the photoelectric sensor is used for acquiring the heart rate of the elderly care users, and the pressure measuring instrument is used for acquiring the blood pressure of the elderly care users.
According to a preferred embodiment of the first aspect of the present invention, the specific collection process of the three meals per day eating volume of each physical elderly care user is to obtain an open time period corresponding to three meals per day by the elderly care institution, and turn on a camera built in an intelligent wearable terminal worn by each physical elderly care user in the corresponding open time period, so as to shoot a video of three meals per day eating by the corresponding physical elderly care user, and further obtain the three meals eating volume from the shot eating video corresponding to three meals per day by each physical elderly care user.
According to a preferred embodiment of the first aspect of the present invention, the method for acquiring the sleep time lengths corresponding to the respective physical care users and the non-self care users is to record according to the intelligent wearable terminals worn by the respective physical care users and the non-self care users.
According to a preferred embodiment of the first aspect of the present invention, the method for acquiring the activity duration of the outdoor activity area corresponding to each physical care user performs the following steps:
h1, positioning the geographical position of the outdoor activity area of the endowment institution;
h2, locating the geographical position of each self-care elderly-care user in real time every day according to a GPS locator built in an intelligent wearable terminal worn by each self-care elderly-care user, matching the geographical position with the geographical position of the outdoor activity area of the elderly-care institution, if the geographical position of a certain time point of a certain self-care elderly-care user is successfully matched with the geographical position of the outdoor activity area of the elderly-care institution, indicating that the geographical position of the self-care elderly-care user at the moment is the outdoor activity area of the elderly-care institution, recording the current time point, recording the time point as the activity starting time point, continuously tracking and locating the geographical position of the self-care elderly-care user at the moment, matching the geographical position of the self-care elderly-care user with the geographical position of the outdoor activity area of the elderly-care institution at the moment, and if the geographical position of the self-care elderly-care user at the certain time point fails to be matched with the geographical position of the outdoor activity area of the elderly-care institution, the self-care elderly people are indicated to leave the outdoor activity area of the elderly people institution at the time point, the current time point is recorded at the moment, and the time point is recorded as the activity ending time point;
h3, subtracting the activity starting time point from the activity ending time point corresponding to each physical and mental user each day to obtain the outdoor activity area activity duration corresponding to each physical and mental user each day.
According to a preferred embodiment of the first aspect of the present invention, the method for acquiring the on-time feeding time coefficient of the corresponding caregiver of each unattended nursing user performs the following steps:
a1, recording the actual feeding time points corresponding to three meals a day for each self-care-free aged-care user in a set monitoring period;
a2, acquiring normal eating time periods corresponding to three meals each day;
a3, comparing the actual feeding time point corresponding to three meals per day of each non-self-care elderly caring user with the normal eating time period corresponding to three meals per day, if the actual feeding time point corresponding to a certain meal of a certain non-self-care elderly caring user is in the normal eating time period corresponding to the meal, the feeding time of the non-self-care elderly caring user corresponding to the meal nursing staff is on time, if the actual feeding time point corresponding to a certain meal of a certain non-self-care elderly caring user is not in the normal eating time period corresponding to the meal, the feeding time of the non-self-care elderly caring user corresponding to the meal nursing staff is not accurate, at the moment, counting the total eating times and the eating times corresponding to the feeding time of each non-self-care elderly caring user in a set monitoring period, and calculating the on-time coefficient of the corresponding nursing staff of each non-self-care caring user in the set monitoring period according to the above, the calculation formula is
Figure BDA0003089908730000051
ηjExpressed as the punctual coefficient of the feeding time of the corresponding nursing staff of the jth self-care elderly-care user in the set monitoring period, fj、FjRespectively representing the number of meals and the total number of meals which correspond to the jth self-service old-age user on time when feeding in a set monitoring period.
According to a preferred embodiment of the first aspect of the present invention, the evaluation process of the physical health coefficient corresponding to the set monitoring period for each physical elderly user is as follows:
b1, acquiring the number of days corresponding to the set monitoring period, recording each day corresponding to the set monitoring period as each monitoring day, numbering each monitoring day according to the time sequence at the moment, and marking the monitoring days as 1,2,. once, k,. once, t in sequence;
b2, forming a three-meal eating amount set Q of the self-care elderly-caring user on the monitoring days by the three-meal eating amounts corresponding to the respective self-care elderly-caring users on the monitoring daysi(qi w1,qi w2,...,qi wk,...,qi wt)，qi wk represents the three-meal food intake of the ith self-care elderly-care user on the kth monitoring day, w represents the three-meal food intake, and w is p1, p2 and p3 which respectively represent the breakfast food intake, the Chinese meal food intake and the dinner food intake;
b3, forming a self-care aged-nursing user monitoring-day physical quality parameter set G by the physical quality parameters corresponding to the respective self-care aged-nursing users in each monitoring dayi(gi u1,gi u2,...,gi uk,...,gi ut)，gi uk is body quality parameters corresponding to the ith self-care elderly user on the kth monitoring day, u is body quality parameters, and u is f1, f2 and f3 which are respectively expressed as heart rate, blood pressure and body temperature;
b4, forming the sleep time length corresponding to each monitoring day by each physical care user into a sleep time length set T of the monitoring day of the physical care useri(Ti1,Ti2,...,Tik,...,Tit),Tik is represented as the sleep duration corresponding to the ith self-care elderly user on the kth monitoring day;
b5, forming the outdoor activity duration set Y of the monitoring days of the self-care elderly users by the outdoor area activity duration corresponding to each monitoring day of the self-care elderly usersi(Yi1,Yi2,...,Yik,...,Yit),Yik represents the activity duration of the outdoor area corresponding to the ith self-care elderly user on the kth monitoring day;
b6, acquiring the age corresponding to each managed elderly user, comparing the three-meal food intake set corresponding to the monitored three-meal daily food intake of the managed elderly user with the standard three-meal food intake of the age group corresponding to the age of the managed elderly user in the aged health database, and acquiring a three-meal daily food intake comparison set delta Q of the monitored three-meal daily food intake comparison set of the managed elderly useri(Δqi w1,Δqi w2,...,Δqi wk,...,Δqi wt) and counting the eating health indexes corresponding to the scheduled monitoring periods of the respective aged-care users according to the formula
Figure BDA0003089908730000061
εiExpressed as the eating health index, delta q, corresponding to the ith self-care elderly user in the set monitoring periodi wk is expressed as the difference between the three-meal food intake of the ith self-care elderly user on the kth monitoring day and the standard three-meal food intake of the age bracket corresponding to the age of the ith self-care elderly user,
Figure BDA0003089908730000062
the standard three-meal food intake is expressed as the standard three-meal food intake of the age corresponding to the age of the ith self-care elderly-care user;
b7, comparing the self-care elderly people monitoring daily physical fitness parameter set with the normal physical fitness parameter values of the age group corresponding to the age of the respective care elderly user in the elderly health database to obtain a self-care elderly people monitoring daily physical fitness parameter comparison set delta Gi(Δgi u1,Δgi u2,...,Δgi uk,...,Δgi ut) and counting the body quality and health indexes of the respective aged-care users in the set monitoring period according to the statistical formula, wherein the calculation formula is
Figure BDA0003089908730000071
σiIs expressed as the body quality and health index, delta g, corresponding to the set monitoring period of the ith self-care elderly useri uk is expressed as the difference between the physical fitness parameter of the ith self-care elderly user on the kth monitoring day and the normal physical fitness parameter of the age corresponding to the age of the self-care elderly user,
Figure BDA0003089908730000072
normal physical quality parameter expressed as age corresponding to the age of the ith self-care elderly userCounting;
b8, calculating the average sleep time per day corresponding to the set monitoring period of each physical aged-care user according to the daily sleep time set monitored by the self-care aged-care users, comparing the average sleep time per day corresponding to the age group corresponding to the age of each physical aged-care user in the aged-care health database, and counting the sleep health indexes corresponding to each physical aged-care user, wherein the calculation formula is
Figure BDA0003089908730000073
λiExpressed as the sleep health index corresponding to the ith self-care elderly user,
Figure BDA0003089908730000074
expressed as the average sleep time per day, T, corresponding to the set monitoring period of the ith self-care elderly-care useri' standard sleep time length of each day corresponding to age of the ith self-care elderly user;
b9, calculating the average outdoor activity duration of each physical endowment user in the set monitoring period according to the set of outdoor activity durations of the self-care endowment users, and comparing the average outdoor activity duration with the activity health indexes corresponding to various outdoor activity durations of the age group corresponding to the age of the physical endowment user in the endowment health database to obtain the activity health indexes corresponding to the physical endowment users in the set monitoring period;
b10, evaluating the corresponding health coefficient of each physical elderly user in the set monitoring period according to the eating health index, the physical fitness health index, the sleep health index and the activity health index of each physical elderly user in the set monitoring period, wherein the calculation formula is
Figure BDA0003089908730000075
Expressed as the body health coefficient, chi, corresponding to the ith self-care elderly user in the set monitoring periodiThe index is expressed as the activity health index corresponding to the ith self-care elderly user in a set monitoring period, and a, b, c and d are respectively expressed as the food intake, physical fitness parameters, sleep and outdoor activity of the self-care elderly userWeight coefficient of influence of physical health.
According to a preferred embodiment of the first aspect of the present invention, the evaluation process of the physical health coefficient of each unattended nursing user in the set monitoring period is as follows:
c1, forming a body quality parameter set G of the monitoring days of the non-self-care elderly users by the body quality parameters corresponding to the monitoring days of the non-self-care elderly usersj(gj u1,gj u2,…,gj uk,...,gj ut)，gj uk is expressed as a physical quality parameter corresponding to the jth self-care-free aged-care user on the kth monitoring day;
c2, forming sleep time length sets T of the monitoring days of the unattended nursing users by the sleep time lengths corresponding to the unattended nursing users on the monitoring daysj(Tj1,Tj2,...,Tjk,...,Tjt),Tjk is represented as the sleep duration corresponding to the jth self-care-free aged-care user on the kth monitoring day;
c3, acquiring the age corresponding to each non-self-care elderly people, comparing the non-self-care elderly people monitoring day physical quality parameter set with the normal physical quality parameter value of the age corresponding to the age of each non-self-care elderly people in the elderly health database, and acquiring the non-self-care elderly people monitoring day physical quality parameter comparison set delta Gj(Δgj u1,Δgj u2,…,Δgj uk,...,Δgj ut) and counting the body quality and health index of each self-care elderly user in the set monitoring period according to the formula
Figure BDA0003089908730000081
σjExpressed as the physical fitness and health index, sigma, corresponding to the jth self-care-free aged-care user in the set monitoring periodjExpressed as the difference between the physical fitness parameter of the jth self-care elderly user on the kth monitoring day and the normal physical fitness parameter of the age corresponding to the age of the self-care elderly user,
Figure BDA0003089908730000082
the normal physical quality parameter is expressed as the normal physical quality parameter of the age group corresponding to the age of the jth self-care elderly-care user;
c4, calculating the average sleep time of each unattended nursing user in the set monitoring period according to the monitored daily sleep time set of the unattended nursing users, comparing the average sleep time with the standard sleep time of each day of the age group corresponding to the age of each unattended nursing user in the nursing health database, and counting the sleep health index corresponding to each unattended nursing user, wherein the calculation formula is
Figure BDA0003089908730000091
λjExpressed as the sleep health index corresponding to the jth self-care elderly people,
Figure BDA0003089908730000092
is expressed as the average sleep time length T 'of the jth self-care-free elderly people corresponding to the set monitoring period'jThe standard sleep time length of each day is expressed as the age corresponding to the age of the jth self-care elderly-care user;
c4, evaluating the body health coefficient of each self-care elderly user in the set monitoring period according to the on-time coefficient, the physical fitness index and the sleep health index of the nursing staff feeding time corresponding to each self-care elderly user in the set monitoring period, wherein the calculation formula is
Figure BDA0003089908730000093
The data are expressed as body health coefficients corresponding to the jth self-care elderly people in a set monitoring period, and x, y and z are expressed as feeding time punctuality, body quality parameters and weight coefficients of influence of sleep on body health of the self-care elderly people.
In a second aspect, the invention provides a smart elderly care user full-period tracking analysis system based on big data and artificial intelligence, which comprises an elderly care user body self-care ability evaluation module, an elderly care user classification module, a self-care elderly care user body health analysis module, a non-self-care elderly care user body health analysis module, an elderly care health database, an analysis server and a display terminal, wherein the elderly care user body self-care ability evaluation module is connected with the elderly care user classification module, the elderly care user classification module is respectively connected with the self-care elderly care user body health analysis module and the non-self-care elderly care user body health analysis module, both the self-care elderly care user body health analysis module and the non-self-care elderly care user body health analysis module are connected with the analysis server, and the analysis server is connected with the display terminal.
In a third aspect, the invention provides a storage medium, wherein a computer program is burned in the storage medium, and when the computer program runs in a memory of a server, the intelligent endowment user full-period tracking analysis method based on big data and artificial intelligence is realized.
Based on any one of the above aspects, the invention has the following beneficial effects:
1. the invention classifies all the aged-care users in the aged-care institution according to the corresponding self-care ability types, thereby obtaining self-care elderly users and non-self-care elderly users, respectively collecting body health parameters of the self-care elderly users and the non-self-care elderly users in a set monitoring period, thereby the healthy parameter to the collection carries out the analysis, assess respectively self-care endowment user and respectively not have self-care endowment user in the healthy coefficient that the settlement monitoring cycle corresponds in the view of the above, realized the endowment user to endowment mechanism endowment corresponds healthy full period tracking analysis, go deep, meticulous endowment mechanism to endowment user's endowment service function, it is comparatively extensive to have compensatied present endowment mechanism endowment service, the not enough drawback of careful degree, the endowment experience of endowment user has been improved, and then the endowment service level of endowment mechanism has been promoted.
2. The method integrates the eating aspect, the physical quality aspect, the sleeping aspect and the outdoor activity aspect of the body health parameters collected by the self-care elderly users and the non-self-care elderly users, the coverage of the collected body health parameters is wide, and comprehensive and reliable evaluation basis can be provided for the evaluation of the later-stage body health coefficient.
3. According to the invention, in the process of collecting the health parameters of the self-care elderly people and the non-self-care elderly people, the intelligent wearable terminals are respectively worn by the self-care elderly people and the non-self-care elderly people to collect the health parameters, the collection mode has high collection efficiency, is more convenient and faster compared with the collection by manual workers, reduces the workload of workers, embodies the characteristic of intelligent collection, and the intelligent wearable terminals are in one-to-one correspondence with the elderly people, so that the repeated collection condition is avoided.
4. According to the invention, after the body health coefficients corresponding to the self-care aged users in the set monitoring period and the body health coefficients corresponding to the self-care aged users in the set monitoring period are evaluated, the self-care aged users and the self-care aged users are classified and sequenced in the body health grade, so that aged care organization service personnel can intuitively know the aged care user distribution conditions corresponding to the body health grade according to the sequencing result, and a reference basis is provided for the targeted service of the aged care users in the later period.
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The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
FIG. 1 is a flow chart of the method steps of the present invention.
Fig. 2 is a schematic diagram of the system module connection according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, in a first aspect, the present invention provides a big data and artificial intelligence based intelligent elderly care user full-period tracking analysis method, including the following steps:
s1, evaluating the self-care ability of the aged-care user: the physical self-care ability evaluation module of the aged care user evaluates the physical self-care ability of the aged care user entering the aged care institution during the stay, determines the type of the physical self-care ability according to the evaluation result, and obtains the type of the physical self-care ability corresponding to each aged care user, wherein the type of the physical self-care ability is divided into a type with self-care ability and a type without self-care ability;
according to the embodiment, the body self-care capability evaluation of the aged-care users entering the aged-care institution during the entering provides classification basis for the subsequent aged-care user classification;
s2, classifying the aged-care users: classifying the aged users corresponding to the same body self-care ability type through an aged user classification module to obtain aged users corresponding to the self-care ability type and aged users corresponding to the non self-care ability type, wherein the aged users corresponding to the self-care ability type are self-care aged users, the aged users corresponding to the non self-care ability type are non-self-care aged users, the aged users are numbered and respectively marked as 1,2, a. The physical quality parameters comprise heart rate, blood pressure and body temperature, the GPS locator is used for locating the geographical position of the elderly user, and the camera is used for collecting the three-meal food intake of the self-care elderly user;
in the embodiment, all the endowment users in the endowment institution are classified, so that the physical health parameters of various endowment users are acquired according to the physical characteristic conditions of the endowment users, and the problem that the evaluation of the physical health coefficient by using uniform physical health parameters is not practical and the authenticity and reliability of the evaluation result are influenced is avoided;
s3, evaluating the body health coefficient of the self-care aged-care user: acquiring the three-meal food intake, the physical quality parameters, the sleep time and the outdoor area activity time corresponding to each physical elderly user in each day in a set monitoring period according to the physical health analysis module of the self-care elderly user;
the specific acquisition process of the food intake of the three meals per day corresponding to each physical endowment user comprises the steps of acquiring an open time period corresponding to three meals per day of an endowment institution, starting a camera built in an intelligent wearable terminal worn by each physical endowment user in the corresponding open time period, shooting a video of three meals per day of the corresponding self-care endowment user, and further acquiring the food intake of the three meals from the shot food videos corresponding to the three meals per day of each physical endowment user;
the method for acquiring the daily body quality parameters corresponding to each physical elderly user comprises the steps of acquiring a body quality parameter acquisition unit which is arranged in an intelligent wearable terminal worn on the body of each physical elderly user, wherein the body quality parameter acquisition unit comprises a thermistor, a photoelectric sensor and a pressure meter, the thermistor is used for acquiring the body temperature of the physical elderly user, the photoelectric sensor is used for acquiring the heart rate of the physical elderly user, and the pressure meter is used for acquiring the blood pressure of the physical elderly user;
the method for acquiring the sleep time of each physical aged-care user every day is to record according to an intelligent wearable terminal worn by each physical aged-care user;
the method for acquiring the activity duration of the outdoor activity area corresponding to each physical aged-care user comprises the following steps:
h1, positioning the geographical position of the outdoor activity area of the endowment institution;
h2, locating the geographical position of each self-care elderly-care user in real time every day according to a GPS locator built in an intelligent wearable terminal worn by each self-care elderly-care user, matching the geographical position with the geographical position of the outdoor activity area of the elderly-care institution, if the geographical position of a certain time point of a certain self-care elderly-care user is successfully matched with the geographical position of the outdoor activity area of the elderly-care institution, indicating that the geographical position of the self-care elderly-care user at the moment is the outdoor activity area of the elderly-care institution, recording the current time point, recording the time point as the activity starting time point, continuously tracking and locating the geographical position of the self-care elderly-care user at the moment, matching the geographical position of the self-care elderly-care user with the geographical position of the outdoor activity area of the elderly-care institution at the moment, and if the geographical position of the self-care elderly-care user at the certain time point fails to be matched with the geographical position of the outdoor activity area of the elderly-care institution, the self-care elderly people are indicated to leave the outdoor activity area of the elderly people institution at the time point, the current time point is recorded at the moment, and the time point is recorded as the activity ending time point;
h3, subtracting the activity starting time point from the activity ending time point corresponding to each physical and mental elderly user each day to obtain the outdoor activity area activity duration corresponding to each physical and mental elderly user each day;
according to the above evaluation, the physical health coefficients of the respective physical care users in the set monitoring period are as follows:
b1, acquiring the number of days corresponding to the set monitoring period, recording each day corresponding to the set monitoring period as each monitoring day, numbering each monitoring day according to the time sequence at the moment, and marking the monitoring days as 1,2,. once, k,. once, t in sequence;
b2, forming a three-meal eating amount set Q of the self-care elderly-caring user on the monitoring days by the three-meal eating amounts corresponding to the respective self-care elderly-caring users on the monitoring daysi(qi w1,qi w2,...,qi wk,…,qi wt)，qi wk represents the three-meal food intake of the ith self-care elderly-care user on the kth monitoring day, w represents the three-meal food intake, and w is p1, p2 and p3 which respectively represent the breakfast food intake, the Chinese meal food intake and the dinner food intake;
b3, forming a self-care aged-nursing user monitoring-day physical quality parameter set G by the physical quality parameters corresponding to the respective self-care aged-nursing users in each monitoring dayi(gi u1,gi u2,…,gi uk,…,gi ut)，gi uk is expressed as the ith self-care elderly user pair on the kth monitoring dayCorresponding physical fitness parameters, u being expressed as physical fitness parameters, u being f1, f2, f3, respectively expressed as heart rate, blood pressure, body temperature;
b4, forming the sleep time length corresponding to each monitoring day by each physical care user into a sleep time length set T of the monitoring day of the physical care useri(Ti1,Ti2,…,Tik,…,Tit),Tik is represented as the sleep duration corresponding to the ith self-care elderly user on the kth monitoring day;
b5, forming the outdoor activity duration set Y of the monitoring days of the self-care elderly users by the outdoor area activity duration corresponding to each monitoring day of the self-care elderly usersi(Yi1,Yi2,…,Yik,…,Yit),Yik represents the activity duration of the outdoor area corresponding to the ith self-care elderly user on the kth monitoring day;
b6, acquiring the age corresponding to each managed elderly user, comparing the three-meal food intake set corresponding to the monitored three-meal daily food intake of the managed elderly user with the standard three-meal food intake of the age group corresponding to the age of the managed elderly user in the aged health database, and acquiring a three-meal daily food intake comparison set delta Q of the monitored three-meal daily food intake comparison set of the managed elderly useri(Δqi w1,Δqi w2,…,Δqi wk,…,Δqi wt) and counting the eating health indexes corresponding to the scheduled monitoring periods of the respective aged-care users according to the formula
Figure BDA0003089908730000141
εiExpressed as the eating health index, delta q, corresponding to the ith self-care elderly user in the set monitoring periodi wk is expressed as the difference between the three-meal food intake of the ith self-care elderly user on the kth monitoring day and the standard three-meal food intake of the age bracket corresponding to the age of the ith self-care elderly user,
Figure BDA0003089908730000142
the standard three-meal food intake is expressed as the standard three-meal food intake of the age corresponding to the age of the ith self-care elderly-caring user, wherein the food intake health coefficient is the maximum and indicates the food intake health degreeThe better;
b7, comparing the self-care elderly people monitoring daily physical fitness parameter set with the normal physical fitness parameter values of the age group corresponding to the age of the respective care elderly user in the elderly health database to obtain a self-care elderly people monitoring daily physical fitness parameter comparison set delta Gi(Δgi u1,Δgi u2,…,Δgi uk,...,Δgi ut) and counting the body quality and health indexes of the respective aged-care users in the set monitoring period according to the statistical formula, wherein the calculation formula is
Figure BDA0003089908730000151
σiIs expressed as the body quality and health index, delta g, corresponding to the set monitoring period of the ith self-care elderly useri uk is expressed as the difference between the physical fitness parameter of the ith self-care elderly user on the kth monitoring day and the normal physical fitness parameter of the age corresponding to the age of the self-care elderly user,
Figure BDA0003089908730000152
the normal physical fitness parameter is expressed as the normal physical fitness parameter of the age corresponding to the age of the ith self-care elderly user, wherein the larger the physical fitness health index is, the better the physical fitness health degree is;
b8, calculating the daily average sleep time length corresponding to the set monitoring period of each physical aged-care user according to the daily sleep time length set monitored by the physical aged-care users
Figure BDA0003089908730000153
And comparing the standard sleep duration of the age group corresponding to the age of the nursing user in the nursing health database, and counting the sleep health index corresponding to the nursing user, wherein the calculation formula is
Figure BDA0003089908730000154
λiExpressed as the sleep health index corresponding to the ith self-care elderly user,
Figure BDA0003089908730000155
expressed as the average sleep time per day, T, corresponding to the set monitoring period of the ith self-care elderly-care useri' expressing the standard sleeping time length of each day corresponding to the age of the ith self-care elderly user, wherein the larger the sleep health index is, the better the sleep health degree is;
b9, calculating the average outdoor activity duration of each physical endowment user in the set monitoring period according to the outdoor activity duration set of the self-care endowment user monitoring day, and comparing the average outdoor activity duration with the activity health indexes corresponding to various outdoor activity durations of the age group corresponding to the age of the physical endowment user in the endowment health database to obtain the activity health indexes corresponding to the physical endowment users in the set monitoring period, wherein the greater the activity health index is, the better the activity health degree is;
b10, evaluating the corresponding health coefficient of each physical elderly user in the set monitoring period according to the eating health index, the physical fitness health index, the sleep health index and the activity health index of each physical elderly user in the set monitoring period, wherein the calculation formula is
Figure BDA0003089908730000161
Expressed as the body health coefficient, chi, corresponding to the ith self-care elderly user in the set monitoring periodiThe activity health index corresponding to the ith self-care elderly user in a set monitoring period is represented as a, b, c and d respectively represent the weight coefficients of the influence of eating, physical fitness parameters, sleeping and outdoor activities of the self-care elderly user on the physical health, wherein the larger the physical health coefficient is, the better the physical health degree is;
s4, evaluating the body health coefficient of the user without self-care for the aged: collecting punctual coefficients of feeding time of nursing staff corresponding to each non-self-care elderly user and physical quality parameters and sleeping time corresponding to each day according to the body health analysis module of the non-self-care elderly user in a set monitoring period;
the method for acquiring the punctual feeding time coefficient of the nursing staff corresponding to each self-care elderly care user comprises the following steps:
a1, recording the actual feeding time points corresponding to three meals a day for each self-care-free aged-care user in a set monitoring period;
a2, acquiring normal eating time periods corresponding to three meals each day;
a3, comparing the actual feeding time point corresponding to three meals per day of each non-self-care elderly caring user with the normal eating time period corresponding to three meals per day, if the actual feeding time point corresponding to a certain meal of a certain non-self-care elderly caring user is in the normal eating time period corresponding to the meal, the feeding time of the non-self-care elderly caring user corresponding to the meal nursing staff is on time, if the actual feeding time point corresponding to a certain meal of a certain non-self-care elderly caring user is not in the normal eating time period corresponding to the meal, the feeding time of the non-self-care elderly caring user corresponding to the meal nursing staff is not accurate, at the moment, counting the total eating times and the eating times corresponding to the feeding time of each non-self-care elderly caring user in a set monitoring period, and calculating the on-time coefficient of the corresponding nursing staff of each non-self-care caring user in the set monitoring period according to the above, the calculation formula is
Figure BDA0003089908730000171
ηjExpressed as the punctual coefficient of the feeding time of the corresponding nursing staff of the jth self-care elderly-care user in the set monitoring period, fj、FjRespectively representing the number of times of eating and the total number of times of eating which correspond to the jth self-care-free aged-care user on time in a set monitoring period, wherein the larger the on-time coefficient of the feeding time is, the better the eating health degree is;
the method for acquiring the daily body quality parameters of each non-self-care elderly user comprises the steps of acquiring according to a body quality parameter acquisition unit built in an intelligent wearable terminal worn by each non-self-care elderly user;
the method for acquiring the sleep time of each non-self-care elderly user every day is characterized in that the sleep time is recorded according to an intelligent wearable terminal worn by each non-self-care elderly user;
according to the above evaluation, the body health coefficient of each self-care elderly care user in the set monitoring period is specifically evaluated as follows:
c1, forming a body quality parameter set G of the monitoring days of the non-self-care elderly users by the body quality parameters corresponding to the monitoring days of the non-self-care elderly usersj(gj u1,gj u2,...,gj uk,...,gj ut)，gj uk is expressed as a physical quality parameter corresponding to the jth self-care-free aged-care user on the kth monitoring day;
c2, forming sleep time length sets T of the monitoring days of the unattended nursing users by the sleep time lengths corresponding to the unattended nursing users on the monitoring daysj(Tj1,Tj2,...,Tjk,...,Tjt),Tjk is represented as the sleep duration corresponding to the jth self-care-free aged-care user on the kth monitoring day;
c3, acquiring the age corresponding to each non-self-care elderly people, comparing the non-self-care elderly people monitoring day physical quality parameter set with the normal physical quality parameter value of the age corresponding to the age of each non-self-care elderly people in the elderly health database, and acquiring the non-self-care elderly people monitoring day physical quality parameter comparison set delta Gj(Δgj u1,Δgj u2,...,Δgj uk,...,Δgj ut) and counting the body quality and health index of each self-care elderly user in the set monitoring period according to the formula
Figure BDA0003089908730000181
σjExpressed as the physical fitness and health index, sigma, corresponding to the jth self-care-free aged-care user in the set monitoring periodjExpressed as the difference between the physical fitness parameter of the jth self-care elderly user on the kth monitoring day and the normal physical fitness parameter of the age corresponding to the age of the self-care elderly user,
Figure BDA0003089908730000182
is expressed as the jth anergyManaging normal physical fitness parameters of age groups corresponding to ages of the aged-caring users;
c4 calculating the average sleep time length of each unattended nursing user in each day corresponding to the set monitoring period according to the sleep time length set of the unattended nursing user
Figure BDA0003089908730000183
And comparing the corresponding standard sleep duration with the standard sleep duration of the age group corresponding to the age of each non-self-care elderly user in the elderly health database, and counting the sleep health index corresponding to each non-self-care elderly user, wherein the calculation formula is
Figure BDA0003089908730000184
λjExpressed as the sleep health index corresponding to the jth self-care elderly people,
Figure BDA0003089908730000185
expressed as the average sleep time per day, T, corresponding to the jth self-care-free aged-care user in the set monitoring periodj' standard sleep time length of each day corresponding to the age of the jth self-care elderly user;
c4, evaluating the body health coefficient of each self-care elderly user in the set monitoring period according to the on-time coefficient, the physical fitness index and the sleep health index of the nursing staff feeding time corresponding to each self-care elderly user in the set monitoring period, wherein the calculation formula is
Figure BDA0003089908730000186
The body health coefficient is expressed as the body health coefficient corresponding to the jth self-care elderly people in a set monitoring period, and x, y and z are expressed as the punctuality of feeding time, the body quality parameters and the weight coefficient of influence of sleep on the body health of the self-care elderly people respectively;
the embodiment integrates the food intake aspect, the body quality aspect, the sleep aspect and the outdoor activity aspect of the body health parameters collected by the self-care elderly users and the non-self-care elderly users, the collected body health parameters cover a wide range, comprehensive and reliable evaluation basis can be provided for evaluation of later-stage body health coefficients, and intelligent wearable terminals are respectively worn on the self-care elderly users and the non-self-care elderly users in the collection process to collect the body health parameters, the collection mode is high in collection efficiency, and compared with collection by manual workers, the collection mode is more convenient and fast, the workload of workers is reduced, the intelligent collection characteristics are reflected, the intelligent wearable terminals correspond to the self-care elderly users one to one, and the situation of repeated collection cannot occur;
the embodiment classifies all the aged-care users in the aged-care institution according to the corresponding self-care ability types, thereby obtaining self-care elderly users and non-self-care elderly users, respectively collecting body health parameters of the self-care elderly users and the non-self-care elderly users in a set monitoring period, the collected physical health parameters are analyzed, and accordingly, the physical health coefficients of the self-care aged users and the non-self-care aged users corresponding to the set monitoring period are evaluated, the full-period tracking analysis of the physical health of the aged users of the aged care institution corresponding to the aged users is realized, the aged care service function of the aged care institution for the aged users is deeply and delicately realized, the defects that the aged care service of the aged care institution is rough and the delicateness degree is insufficient at present are greatly overcome, the aged care experience of the aged users is improved, and the aged care service level of the aged care institution is further improved;
s5, acquiring the body health grade of the aged-care user: comparing the body health coefficient corresponding to each self-care elderly user in the set monitoring period with the body health coefficient range corresponding to various body health grades of the self-care elderly user in the elderly health database through the analysis server to obtain the body health grade corresponding to each self-care elderly user in the set monitoring period, and comparing the body health coefficient corresponding to each non-self-care elderly user in the set monitoring period with the body health coefficient range corresponding to various body health grades of the non-self-care elderly user in the elderly health database to obtain the body health grade corresponding to each non-self-care elderly user in the set monitoring period;
s6, classifying the physical health grade of the aged-care user: comparing the body health grade corresponding to each physical endowment user in a set monitoring period with the body health grade corresponding to each non-self-care endowment user in the set monitoring period through an analysis server, so as to collect the self-care endowment users corresponding to the same body health grade and the non-self-care endowment users corresponding to the same body health grade, and obtain a self-care endowment user set corresponding to various body health grades and a non-self-care endowment user set corresponding to various body health grades;
s7, displaying the body health grade of the aged-care user: the self-care elderly care user sets corresponding to various body health levels and the non-self-care elderly care user sets corresponding to various body health levels are sequenced from large to small according to the body health levels through the display terminal, sequencing results of the self-care elderly care user sets corresponding to various body health levels and sequencing results of the non-self-care elderly care user sets corresponding to various body health levels are obtained, the sequencing results are displayed, and therefore elderly care organization service personnel can conveniently and visually know distribution conditions of elderly care users corresponding to various body health levels according to the sequencing results, and reference basis is further provided for targeted service of elderly care users in the later period.
Referring to fig. 2, in a second aspect, the invention provides a smart elderly care user full-period tracking analysis system based on big data and artificial intelligence, which comprises an elderly care user body self-care capability evaluation module, an elderly care user classification module, a self-care elderly care user body health analysis module, a non-self-care elderly care user body health analysis module, an elderly care health database, an analysis server and a display terminal, wherein the elderly care user body self-care capability evaluation module is connected with the elderly care user classification module, the elderly care user classification module is respectively connected with the self-care elderly care user body health analysis module and the non-self-care elderly care user body health analysis module, the self-care elderly care user body health analysis module and the non-self-care elderly care user body health analysis module are both connected with the analysis server, and the analysis server is connected with the display terminal.
In a third aspect, the invention provides a storage medium, wherein a computer program is burned in the storage medium, and when the computer program runs in a memory of a server, the intelligent endowment user full-period tracking analysis method based on big data and artificial intelligence is realized.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.

Claims (10)

1. The intelligent old-age user full-period tracking analysis method based on big data and artificial intelligence is characterized by comprising the following steps of:
s1, evaluating the self-care ability of the aged-care user: the physical self-care ability evaluation module is used for evaluating the physical self-care ability of the aged-care users who live in the aged-care institution during the live in, and determining the types of the physical self-care ability according to the evaluation result to obtain the types of the physical self-care ability corresponding to the aged-care users;
s2, classifying the aged-care users: classifying the aged users corresponding to the same body self-care ability type through an aged user classification module to obtain aged users corresponding to the self-care ability type and aged users corresponding to the non self-care ability type, wherein the aged users corresponding to the self-care ability type are marked as self-care aged users, the aged users corresponding to the non self-care ability type are marked as non-self-care aged users, at the moment, the aged users are numbered respectively as 1,2, a.
S3, evaluating the body health coefficient of the self-care aged-care user: collecting three-meal food intake, physical quality parameters, sleeping time and outdoor area activity time corresponding to each physical elderly user every day in a set monitoring period according to the physical health analysis module of the self-care elderly users, and evaluating the physical health coefficients corresponding to each physical elderly user in the set monitoring period according to the three-meal food intake, the physical quality parameters, the sleeping time and the outdoor area activity time;
s4, evaluating the body health coefficient of the user without self-care for the aged: collecting an on-time coefficient of feeding time of a nursing staff corresponding to each non-self-care elderly user and a physical quality parameter and a sleeping time length corresponding to each day according to the body health analysis module of the non-self-care elderly user in a set monitoring period, and evaluating the body health coefficient corresponding to each non-self-care elderly user in the set monitoring period according to the on-time coefficient;
s5, acquiring the body health grade of the aged-care user: comparing the body health coefficient corresponding to each self-care elderly user in the set monitoring period with the body health coefficient range corresponding to various body health grades of the self-care elderly user in the elderly health database through the analysis server to obtain the body health grade corresponding to each self-care elderly user in the set monitoring period, and comparing the body health coefficient corresponding to each non-self-care elderly user in the set monitoring period with the body health coefficient range corresponding to various body health grades of the non-self-care elderly user in the elderly health database to obtain the body health grade corresponding to each non-self-care elderly user in the set monitoring period;
s6, classifying the physical health grade of the aged-care user: comparing the body health grade corresponding to each physical endowment user in a set monitoring period with the body health grade corresponding to each non-self-care endowment user in the set monitoring period through an analysis server, so as to collect the self-care endowment users corresponding to the same body health grade and the non-self-care endowment users corresponding to the same body health grade, and obtain a self-care endowment user set corresponding to various body health grades and a non-self-care endowment user set corresponding to various body health grades;
s7, displaying the body health grade of the aged-care user: sequencing the self-care elderly care user sets corresponding to various body health levels and the non-self-care elderly care user sets corresponding to various body health levels from large to small according to the body health levels through the display terminal, obtaining sequencing results of the self-care elderly care user sets corresponding to various body health levels and sequencing results of the non-self-care elderly care user sets corresponding to various body health levels, and displaying the sequencing results.
2. The intelligent elderly-care user full-period tracking and analyzing method based on big data and artificial intelligence of claim 1, wherein: the method for collecting the corresponding body quality parameters of the self-care elderly users and the non-self-care elderly users is characterized in that the self-care elderly users and the non-self-care elderly users are respectively worn with an intelligent wearable terminal, a body quality parameter collecting unit, a GPS (global positioning system) locator and a camera are arranged in the intelligent wearable terminal, the body quality parameter collecting unit comprises a thermistor, a photoelectric sensor and a pressure measuring instrument, the thermistor is used for collecting the body temperature of the elderly users, the photoelectric sensor is used for collecting the heart rate of the elderly users, and the pressure measuring instrument is used for collecting the blood pressure of the elderly users.
3. The intelligent elderly-care user full-period tracking and analyzing method based on big data and artificial intelligence of claim 1, wherein: the specific acquisition process that each kind of reason endowment user corresponds three meals food intake every day is for obtaining the open time quantum that endowment mechanism three meals every day correspond to open the built-in camera of the intelligent wearing terminal that each kind of reason endowment user dressed on one's body in the open time quantum that corresponds, be used for shooing the video that corresponds the three meals of self-care endowment user every day feed, and then obtain three meals food intake from the food video that each kind of reason endowment user who shoots corresponds three meals every day.
4. The intelligent elderly-care user full-period tracking and analyzing method based on big data and artificial intelligence of claim 1, wherein: the method for acquiring the sleep time length corresponding to each self-care elderly care user and each non-self-care elderly care user is used for recording according to the intelligent wearable terminals worn by each self-care elderly care user and each non-self-care elderly care user.
5. The intelligent elderly-care user full-period tracking and analyzing method based on big data and artificial intelligence of claim 1, wherein: the method for acquiring the activity duration of the outdoor activity area corresponding to each physical aged-care user executes the following steps:
h1, positioning the geographical position of the outdoor activity area of the endowment institution;
h2, locating the geographical position of each self-care elderly-care user in real time every day according to a GPS locator built in an intelligent wearable terminal worn by each self-care elderly-care user, matching the geographical position with the geographical position of the outdoor activity area of the elderly-care institution, if the geographical position of a certain time point of a certain self-care elderly-care user is successfully matched with the geographical position of the outdoor activity area of the elderly-care institution, indicating that the geographical position of the self-care elderly-care user at the moment is the outdoor activity area of the elderly-care institution, recording the current time point, recording the time point as the activity starting time point, continuously tracking and locating the geographical position of the self-care elderly-care user at the moment, matching the geographical position of the self-care elderly-care user with the geographical position of the outdoor activity area of the elderly-care institution at the moment, and if the geographical position of the self-care elderly-care user at the certain time point fails to be matched with the geographical position of the outdoor activity area of the elderly-care institution, the self-care elderly people are indicated to leave the outdoor activity area of the elderly people institution at the time point, the current time point is recorded at the moment, and the time point is recorded as the activity ending time point;
h3, subtracting the activity starting time point from the activity ending time point corresponding to each physical and mental user each day to obtain the outdoor activity area activity duration corresponding to each physical and mental user each day.
6. The intelligent elderly-care user full-period tracking and analyzing method based on big data and artificial intelligence of claim 1, wherein: the method for acquiring the punctual feeding time coefficient of the nursing staff corresponding to each self-care elderly care user comprises the following steps:
a1, recording the actual feeding time points corresponding to three meals a day for each self-care-free aged-care user in a set monitoring period;
a2, acquiring normal eating time periods corresponding to three meals each day;
a3, comparing the actual feeding time points corresponding to the three meals per day of each non-self-care elderly person user with the normal eating time periods corresponding to the three meals per day, and if the actual feeding time points corresponding to a certain meal of a certain non-self-care elderly person user are within the normal eating time periods corresponding to the meal, comparing the actual feeding time points corresponding to the three meals per day of the non-self-care elderly person user with the normal eating time periods corresponding to the meal, wherein the actual feeding time points corresponding to the non-self-care elderly person user are within the normal eating time periods corresponding to the mealThe feeding time of the nursing staff is on time, if the actual feeding time point corresponding to a certain meal of a self-care elderly user is not in the normal feeding time period corresponding to the meal, the feeding time of the self-care elderly user corresponding to the nursing staff is not accurate, at the moment, the total eating times and the feeding time on time corresponding to the feeding time of the self-care elderly user in a set monitoring period are counted, the on-time coefficient of the feeding time of the nursing staff corresponding to the self-care elderly user in the set monitoring period is calculated according to the total eating times and the feeding time on time of the self-care elderly user, and the calculation formula is that
Figure FDA0003089908720000041
ηjExpressed as the punctual coefficient of the feeding time of the corresponding nursing staff of the jth self-care elderly-care user in the set monitoring period, fj、FjRespectively representing the number of meals and the total number of meals which correspond to the jth self-service old-age user on time when feeding in a set monitoring period.
7. The intelligent elderly-care user full-period tracking and analyzing method based on big data and artificial intelligence of claim 1, wherein: the evaluation process of the body health coefficient corresponding to the physical care user in the set monitoring period is as follows:
b1, acquiring the number of days corresponding to the set monitoring period, recording each day corresponding to the set monitoring period as each monitoring day, numbering each monitoring day according to the time sequence at the moment, and marking the monitoring days as 1,2,. once, k,. once, t in sequence;
b2, forming a three-meal eating amount set Q of the self-care elderly-caring user on the monitoring days by the three-meal eating amounts corresponding to the respective self-care elderly-caring users on the monitoring daysi(qi w1,qi w2,...,qi wk,...,qi wt)，qi wk represents the three-meal food intake of the ith self-care elderly-care user on the kth monitoring day, w represents the three-meal food intake, and w is p1, p2 and p3 which respectively represent the breakfast food intake, the Chinese meal food intake and the dinner food intake;
b3 use of the herbs for treating and nourishing the agedThe physical quality parameters corresponding to each monitoring day of the user form a physical quality parameter set G of the self-care endowment user monitoring dayi(gi u1,gi u2,...,gi uk,...,gi ut)，gi uk is body quality parameters corresponding to the ith self-care elderly user on the kth monitoring day, u is body quality parameters, and u is f1, f2 and f3 which are respectively expressed as heart rate, blood pressure and body temperature;
b4, forming the sleep time length corresponding to each monitoring day by each physical care user into a sleep time length set T of the monitoring day of the physical care useri(Ti1,Ti2,...,Tik,...,Tit),Tik is represented as the sleep duration corresponding to the ith self-care elderly user on the kth monitoring day;
b5, forming the outdoor activity duration set Y of the monitoring days of the self-care elderly users by the outdoor area activity duration corresponding to each monitoring day of the self-care elderly usersi(Yi1,Yi2,...,Yik,...,Yit),Yik represents the activity duration of the outdoor area corresponding to the ith self-care elderly user on the kth monitoring day;
b6, acquiring the age corresponding to each managed elderly user, comparing the three-meal food intake set corresponding to the monitored three-meal daily food intake of the managed elderly user with the standard three-meal food intake of the age group corresponding to the age of the managed elderly user in the aged health database, and acquiring a three-meal daily food intake comparison set delta Q of the monitored three-meal daily food intake comparison set of the managed elderly useri(Δqi w1,Δqi w2,...,Δqi wk,...,Δqi wt) and counting the eating health indexes corresponding to the scheduled monitoring periods of the respective aged-care users according to the formula
Figure FDA0003089908720000061
εiExpressed as the eating health index, delta q, corresponding to the ith self-care elderly user in the set monitoring periodi wk represents the three-meal food intake of the ith self-care elderly user on the kth monitoring day and the year corresponding to the age of the self-care elderly userThe difference between the standard three meal meals for the age group,
Figure FDA0003089908720000062
the standard three-meal food intake is expressed as the standard three-meal food intake of the age corresponding to the age of the ith self-care elderly-care user;
b7, comparing the self-care elderly people monitoring daily physical fitness parameter set with the normal physical fitness parameter values of the age group corresponding to the age of the respective care elderly user in the elderly health database to obtain a self-care elderly people monitoring daily physical fitness parameter comparison set delta Gi(Δgi u1,Δgi u2,...,Δgi uk,...,Δgi ut) and counting the body quality and health indexes of the respective aged-care users in the set monitoring period according to the statistical formula, wherein the calculation formula is
Figure FDA0003089908720000063
σiIs expressed as the body quality and health index, delta g, corresponding to the set monitoring period of the ith self-care elderly useri uk is expressed as the difference between the physical fitness parameter of the ith self-care elderly user on the kth monitoring day and the normal physical fitness parameter of the age corresponding to the age of the self-care elderly user,
Figure FDA0003089908720000064
the normal physical quality parameter is expressed as the normal physical quality parameter of the age corresponding to the age of the ith self-care elderly user;
b8, calculating the average sleep time per day corresponding to the set monitoring period of each physical aged-care user according to the daily sleep time set monitored by the self-care aged-care users, comparing the average sleep time per day corresponding to the age group corresponding to the age of each physical aged-care user in the aged-care health database, and counting the sleep health indexes corresponding to each physical aged-care user, wherein the calculation formula is
Figure FDA0003089908720000065
λiExpressed as the ith autotrophic cultureThe sleep health index corresponding to the old user,
Figure FDA0003089908720000066
expressed as the average sleep time per day, T, corresponding to the set monitoring period of the ith self-care elderly-care useri' standard sleep time length of each day corresponding to age of the ith self-care elderly user;
b9, calculating the average outdoor activity duration of each physical endowment user in the set monitoring period according to the set of outdoor activity durations of the self-care endowment users, and comparing the average outdoor activity duration with the activity health indexes corresponding to various outdoor activity durations of the age group corresponding to the age of the physical endowment user in the endowment health database to obtain the activity health indexes corresponding to the physical endowment users in the set monitoring period;
b10, evaluating the corresponding health coefficient of each physical elderly user in the set monitoring period according to the eating health index, the physical fitness health index, the sleep health index and the activity health index of each physical elderly user in the set monitoring period, wherein the calculation formula is
Figure FDA0003089908720000071
Figure FDA0003089908720000072
Expressed as the body health coefficient, chi, corresponding to the ith self-care elderly user in the set monitoring periodiThe index is expressed as the activity health index corresponding to the ith self-care elderly user in a set monitoring period, and a, b, c and d are respectively expressed as the weight coefficients of the influence of eating, physical fitness parameters, sleeping and outdoor activities of the self-care elderly user on the physical health.
8. The intelligent elderly-care user full-period tracking and analyzing method based on big data and artificial intelligence of claim 1, wherein: the evaluation process of the body health coefficient corresponding to each self-care elderly user in the set monitoring period is as follows:
c1 reaction ofThe physical quality parameters corresponding to each monitoring day of each non-self-care elderly user form a physical quality parameter set G of the monitoring day of the non-self-care elderly userj(gj u1,gj u2,...,gj uk,...,gj ut)，gj uk is expressed as a physical quality parameter corresponding to the jth self-care-free aged-care user on the kth monitoring day;
c2, forming sleep time length sets T of the monitoring days of the unattended nursing users by the sleep time lengths corresponding to the unattended nursing users on the monitoring daysj(Tj1,Tj2,...,Tjk,...,Tjt),Tjk is represented as the sleep duration corresponding to the jth self-care-free aged-care user on the kth monitoring day;
c3, acquiring the age corresponding to each non-self-care elderly people, comparing the non-self-care elderly people monitoring day physical quality parameter set with the normal physical quality parameter value of the age corresponding to the age of each non-self-care elderly people in the elderly health database, and acquiring the non-self-care elderly people monitoring day physical quality parameter comparison set delta Gj(Δgj u1,Δgj u2,...,Δgj uk,...,Δgj ut) and counting the body quality and health index of each self-care elderly user in the set monitoring period according to the formula
Figure FDA0003089908720000081
σjExpressed as the physical fitness and health index, sigma, corresponding to the jth self-care-free aged-care user in the set monitoring periodjExpressed as the difference between the physical fitness parameter of the jth self-care elderly user on the kth monitoring day and the normal physical fitness parameter of the age corresponding to the age of the self-care elderly user,
Figure FDA0003089908720000082
the normal physical quality parameter is expressed as the normal physical quality parameter of the age group corresponding to the age of the jth self-care elderly-care user;
c4 according to the monitoring day of the non-self-care old-aged peopleThe sleep duration set calculates the daily average sleep duration corresponding to each unattended nursing user in a set monitoring period, the daily average sleep duration corresponding to each unattended nursing user is compared with the daily standard sleep duration of the age group corresponding to the age of each unattended nursing user in the nursing health database, the sleep health index corresponding to each unattended nursing user is counted, and the calculation formula is that
Figure FDA0003089908720000083
λjExpressed as the sleep health index corresponding to the jth self-care elderly people,
Figure FDA0003089908720000084
expressed as the average sleep time per day, T, corresponding to the jth self-care-free aged-care user in the set monitoring periodj' standard sleep time length of each day corresponding to the age of the jth self-care elderly user;
c4, evaluating the body health coefficient of each self-care elderly user in the set monitoring period according to the on-time coefficient, the physical fitness index and the sleep health index of the nursing staff feeding time corresponding to each self-care elderly user in the set monitoring period, wherein the calculation formula is
Figure FDA0003089908720000085
Figure FDA0003089908720000086
The data are expressed as body health coefficients corresponding to the jth self-care elderly people in a set monitoring period, and x, y and z are expressed as feeding time punctuality, body quality parameters and weight coefficients of influence of sleep on body health of the self-care elderly people.
9. The utility model provides an intelligence endowment user complete cycle tracking analytic system based on big data and artificial intelligence which characterized in that: the system comprises an aged care user body self-care ability evaluation module, an aged care user classification module, a self-care aged care user body health analysis module, a non-self-care aged care user body health analysis module, an aged care health database, an analysis server and a display terminal, wherein the aged care user body self-care ability evaluation module is connected with the aged care user classification module, the aged care user classification module is respectively connected with the self-care aged care user body health analysis module and the non-self-care aged care user body health analysis module, the self-care aged care user body health analysis module and the non-self-care aged care user body health analysis module are both connected with the analysis server, and the analysis server is connected with the display terminal.
10. A storage medium, characterized by: the storage medium is burned with a computer program, and the computer program realizes the method of any one of the above claims 1-8 when running in the memory of the server.
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