CN106777872A - A kind of method that life of elderly person quality evaluation is carried out based on intelligent wearing technology - Google Patents
A kind of method that life of elderly person quality evaluation is carried out based on intelligent wearing technology Download PDFInfo
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Abstract
The invention discloses a kind of method for carrying out life of elderly person quality evaluation based on intelligent wearing technology, it is related to intelligence wearing technical field.By using Intelligent worn device and intelligent terminal gathered data, comprehensive items body state analyzes the quality of life of guardianship, and the thinking of the type, mode and analyze data of its gathered data all has very big difference with classical evaluation method.This evaluation method has the following advantages：Gathered data is accurate, objective；Drain on manpower and material resources is greatly lowered；The change of data can in time be found.
Description
Technical Field
The invention relates to the technical field of intelligent wearing, in particular to a method for evaluating the life quality of old people based on an intelligent wearing technology.
Background
Along with the arrival of aging society, the burden of national endowment is gradually increased, and in order to conveniently and effectively monitor the old, a lot of intelligent wearing equipment serving the old appears on the market.
At present, the intelligent wearable device can acquire physiological indexes of the old, such as blood pressure and blood sugar, and some intelligent wearable devices also have functions of positioning, falling reminding and data acquisition of activity and sleep conditions of the old, but lack of acquisition of relevant data of psychological and social factors of the old. The WHO considers that human health includes physiological, psychological and social factors, and comprehensively evaluates the health of the old people to include the factors. Therefore, the prior art lacks an intelligent technology for effectively evaluating the life state and health condition of the old.
Disclosure of Invention
The invention aims to provide a method for evaluating the life quality of the old people based on an intelligent wearing technology, so that the problems in the prior art are solved.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
a method for evaluating the life quality of the old based on an intelligent wearing technology comprises the following steps:
s1, determining the index for evaluating the life quality of the old, comprising: physiological function indexes, psychological function indexes and social function indexes, and acquiring composition factors and data of each index, and synchronizing all the acquired data into a database of the intelligent health platform;
s2, judging whether the data volume of each index in the database reaches a threshold value, if so, jumping to S3, otherwise, jumping to S1;
s3, carrying out non-dimensionalization treatment on all the composition factors according to the characteristics of different composition factors, carrying out forward conversion on the reverse indexes, and calculating the score of each composition factor;
s4, adding the scores of the composition factors to obtain an aged activity index score; and evaluating the life quality of the old according to the score of the activity index of the old.
Preferably, the composition factors of the physiological function index include: physiological function indexes which can be measured by intelligent wearing technologies such as age, gender, body pain/discomfort, chronic disease types, blood pressure, blood sugar, respiration, heart rate, eyesight, hearing and the like;
the psychological function index comprises the following components: indexes which can measure and reflect psychological functions of intelligent wearing technologies such as cognition, emotion, appetite, sleep and the like;
the composition factors of the social function include: the intelligent wearing technologies such as education level, medical insurance, occupation, income, presence or absence of spouse, social interaction, exercise level and the like can be measured or indexes reflecting social functions can be obtained through an intelligent health platform.
Preferably, in the composition factors, data of age, sex, education degree, medical insurance condition, occupation, income, spouse existence and chronic disease category are directly acquired through the intelligent health platform; data of blood pressure, blood sugar, respiration, heart rate, vision, hearing, emotion, appetite, sleep, social interaction and exercise level are acquired through the intelligent wearable device and synchronized to the intelligent health platform; the data of the subjective life satisfaction of the old, the vision, the hearing and the body pain/discomfort are obtained through the intelligent terminal.
Preferably, in S2, the threshold is 400.
Preferably, S3 is specifically:
the composition factors comprise qualitative factors and quantitative factors, and the quantitative factors are divided into linear type factors, broken line type factors and curve type factors;
the scores of the qualitative factors convert the conversion values into numbers according to the characteristics of the composition factors;
the score of the linear factor is calculated by adopting the following formula:
wherein,
the score of the broken line type factor is calculated by adopting the following formula:
the score of the curve form factor is calculated based on the characteristics of the composition factors.
Preferably, the method further comprises the following step of S4: and S5, performing exploratory factor analysis on the data processed in the S3, and determining an index which has a large influence on the activity index of the elderly.
Preferably, S5 specifically includes the following steps:
s501, constructing a covariance matrix by adopting a principal component analysis method and a maximum variance orthogonal rotation method:
wherein,
X1,X2,…，Xkrepresents k measurable index variables representing the number of k measurable index variables,
Rijrepresenting the correlation coefficient between k index variables;
s502, according to the calculation result of the covariance matrix, according to the following formula:
|λE-R|＝0，
calculating the eigenvalue lambdaiPrincipal component ZiThe contribution ratio of (c):and cumulative contribution rate:
s503, screening the characteristic value lambdai>1, a public factor with the cumulative contribution rate of more than 80 percent;
s504, a possible senile vitality index theoretical model is provided for each public factor;
and S505, calculating the absolute fitting index of each aging activity index theoretical model by using AMOS software and adopting a maximum likelihood estimation method: x is the number of2GFI, RMR, SRMR, RMSEA; relative fitting index: NFI, TLI, CFI; information fitting index: AIC, CAI C;
s506, judging whether the fitting index meets the evaluation standard, if so, jumping to S507, otherwise, jumping to S504;
and S507, determining an old age vitality index theoretical model corresponding to the fitting index, and analyzing indexes which have large influence on the old age vitality index according to the old age vitality index theoretical model.
The invention has the beneficial effects that: according to the method for evaluating the life quality of the elderly based on the intelligent wearing technology, the intelligent wearing equipment and the intelligent terminal are used for acquiring data, the life quality of the monitored object is analyzed by integrating various human body states, and the type and the mode of the acquired data and the thought of analyzing the data are greatly different from those of a classical evaluation mode. This way of evaluation has the following advantages: the collected data is accurate and objective; the consumption of manpower and material resources is greatly reduced; the change of the data can be found in time.
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FIG. 1 is a schematic process flow diagram.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention.
In the evaluation of the quality of life of the old, the majority of ways need to adopt subjective evaluation, and the quality of life measurement is considered to contain subjective indexes,
the old people in China generally have the following characteristics: chronic diseases are not cured; the empty nest proportion is high, and most of the empty nests need different degrees of care; there are different degrees of decline in motor function and cognitive ability; there is often a decrease in social level; strong self-esteem, psychological sensitivity and the like.
Because of the relation of some old man because of ageing and some diseases, there is not enough cognitive ability, be difficult to understand its meaning, also be difficult to judge the life state of self rationally, in addition, in the process of appraising, when answering relevant questions, there is the tendency of modifying the answer because of reasons such as self-esteem more easily, so, the mode of obtaining old man's life state information through the mode of problem that often uses at present, it is not objective enough, lead to the data to be inaccurate, thereby can't effectual evaluation old man's health index, simultaneously, the mode of questionnaire also is time-consuming and laborious, with high costs, can't obtain old man's health index data in time, be unfavorable for the guardianship to old man.
And if the physiological data acquired by the current intelligent wearable equipment is adopted, the health condition of the old people cannot be comprehensively reflected.
Therefore, in order to solve the problems, the invention objectively collects the life performance index data of the old people such as exercise level, social activities and the like, the physiological performance index data of sleep, blood pressure, blood sugar, eyesight, hearing and the like, and the social data index data of education degree, industrial income and the like in real time, and makes overall evaluation on the life state of the old people to form an evaluation result which is fast and accurate and changes in real time along with the current situation of the old people. The life quality evaluation mode is beneficial to understanding the life quality of the old, formulating the welfare policy for the aged, evaluating the service quality of the aged, and the like. Meanwhile, the evaluation method can be used for intelligent endowment monitoring, manpower and material resources required by monitoring are reduced, and the endowment service accuracy is improved.
As shown in fig. 1, an embodiment of the present invention provides a method for evaluating life quality of an elderly person based on an intelligent wearing technology, including the following steps:
s1, determining the index for evaluating the life quality of the old, comprising: physiological function indexes, psychological function indexes and social function indexes, and acquiring composition factors and data of each index, and synchronizing all the acquired data into a database of the intelligent health platform;
s2, judging whether the data volume of each index in the database reaches a threshold value, if so, jumping to S3, otherwise, jumping to S1;
s3, carrying out non-dimensionalization treatment on all the composition factors according to the characteristics of different composition factors, carrying out forward conversion on the reverse indexes, and calculating the score of each composition factor;
s4, adding the scores of the composition factors to obtain an aged activity index score; and evaluating the life quality of the old according to the score of the activity index of the old.
Wherein, the composition factors of the physiological function index comprise: physiological function indexes which can be measured by intelligent wearing technologies such as age, gender, body pain/discomfort, chronic disease types, blood pressure, blood sugar, respiration, heart rate, eyesight, hearing and the like;
the psychological function index comprises the following components: indexes which can measure and reflect psychological functions of intelligent wearing technologies such as cognition, emotion, appetite, sleep and the like;
the composition factors of the social function include: the intelligent wearing technologies such as education level, medical insurance, occupation, income, presence or absence of spouse, social interaction, exercise level and the like can be measured or indexes reflecting social functions can be obtained through an intelligent health platform.
In the composition factors, data such as age, sex, education degree, medical insurance condition, occupation, income, spouse existence, chronic disease category and the like are directly acquired through the intelligent health platform; data of blood pressure, blood sugar, respiration, heart rate, vision, hearing, emotion, appetite, sleep, social interaction and exercise level are acquired through the intelligent wearable device and synchronized to the intelligent health platform; the data of the subjective life satisfaction of the old, the vision, the hearing and the body pain/discomfort are obtained through the intelligent terminal.
In this embodiment, the composition factors of each index and the manner of acquiring the data thereof may be shown in the following table:
the intelligent terminal can be any terminal with the function of collecting the data.
In the case of being unable to be measured directly, the above factors can be converted into other directly measurable factors. For example: social interactions may include factors such as the number of times the smart wearable device calculates interactions with others using the smart terminal, the degree of variability of the outgoing route, the time of the verbal communication, etc.
In the embodiment of the present invention, in S2, the threshold may be 400, that is, after the data amount of each index in the database reaches 400 sets of data, subsequent analysis and calculation may be performed.
And if the data amount of each index is too small, the statistical result is not credible.
In the embodiment of the present invention, the first and second substrates,
s3 specifically includes:
the composition factors comprise qualitative factors and quantitative factors, and the quantitative factors are divided into linear type factors, broken line type factors and curve type factors;
the scores of the qualitative factors convert the conversion values into numbers according to the characteristics of the composition factors;
the score of the linear factor is calculated by adopting the following formula:
wherein,
the score of the broken line type factor is calculated by adopting the following formula:
the score of the curve form factor is calculated based on the characteristics of the composition factors.
Specifically, the formulas and features that can be used are shown in the following table:
for example, sleep time factor: through expert evaluation, the sleep time of 7-8 hours is considered to be the most beneficial to health, and the quality of life is reduced due to too short or too long sleep time. The sleep time factor is qualitatively broken line type factor, and the dimensionless calculation method is as follows:
in a preferred embodiment of the present invention, the step of S4 may further include the following steps: and S5, performing exploratory factor analysis on the data processed in the S3, and determining an index which has a large influence on the activity index of the elderly.
According to the index which has a large influence on the activity index of the old people, the life quality of the old people can be improved by improving the index.
In a preferred embodiment of the present invention, S5 specifically includes the following steps:
s501, constructing a covariance matrix by adopting a principal component analysis method and a maximum variance orthogonal rotation method:
wherein,
X1,X2,…，Xkrepresents k measurable index variables representing the number of k measurable index variables,
Rijrepresenting the correlation coefficient between k index variables;
s502, according to the calculation result of the covariance matrix, according to the following formula:
|λE-R|＝0，
calculating the eigenvalue lambdaiPrincipal component ZiThe contribution ratio of (c):and cumulative contribution rate:
s503, screening the characteristic value lambdai>1, a public factor with the cumulative contribution rate of more than 80 percent;
s504, a possible senile vitality index theoretical model is provided for each public factor;
and S505, calculating the absolute fitting index of each aging activity index theoretical model by using AMOS software and adopting a maximum likelihood estimation method: x is the number of2GFI, RMR, SRMR, RMSEA; relative fitting index: NFI, TLI, CFI; information fitting index: AIC, CAI C;
s506, judging whether the fitting index meets the evaluation standard, if so, jumping to S507, otherwise, jumping to S504;
and S507, determining an old age vitality index theoretical model corresponding to the fitting index, and analyzing indexes which have large influence on the old age vitality index according to the old age vitality index theoretical model.
Wherein, the absolute fitting index is: goodness of fit test x2The goodness-of-fit index GFI, the root mean square residual error RMR, the standard root mean square residual error SRMR and the root mean square error RMSEA of the approximate error; relative fitting index: standardizing a fitting index NFI, a Tucker-Lewis index TLI and a comparative fitting index CFI; information fitting index: an information standard index AI C, a continuous information standard index CAI C.
The evaluation criteria in S506 may be as shown in the following table:
the invention adopts some evaluation items in the classic quality of life evaluation scale, and the existing research proves that the items have obvious correlation with the quality of life. The technical characteristics of the evaluation mode based on the intelligent wearable equipment and the health platform are that the acquired data volume is large, and the life aspect of an evaluated person can be covered, so most factors related to the life quality of the old are included in the evaluation system through different acquisition modes through research verification, and a more accurate and three-dimensional novel evaluation mode is formed; meanwhile, as the data volume in the health platform database continuously increases along with the use degree, a dynamic and growth-possessing evaluation algorithm is formed by continuously carrying out verification factor analysis and exploratory factor analysis so as to adapt to different social environments and value systems.
By adopting the technical scheme disclosed by the invention, the following beneficial effects are obtained: according to the method for evaluating the life quality of the elderly based on the intelligent wearing technology, the intelligent wearing equipment and the intelligent terminal are used for acquiring data, the life quality of the monitored object is analyzed by integrating various human body states, and the type and the mode of the acquired data and the thought of analyzing the data are greatly different from those of a classical evaluation mode. This way of evaluation has the following advantages: the collected data is accurate and objective; the consumption of manpower and material resources is greatly reduced; the change of the data can be found in time.
By adopting the method provided by the embodiment of the invention, the following steps can be carried out: the existing endowment service providing mode is reformed, more pertinence is achieved, the service quality is improved, and meanwhile, the resource waste is reduced; the family members who cannot live together or lack the time to live together with the old people can know the living state of the old people conveniently, and the living safety and the social support degree of the old people are improved; the popular and easily understood vitality index is formed, the comparison by the old is convenient, and the attention of the old to the physiological indexes such as blood pressure, blood sugar and the like is transferred to the quality of life and the sense of happiness. The initiative is fully exerted, and the life quality of the user is improved.
The embodiments in the present specification are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
It should be understood by those skilled in the art that the timing sequence of the method steps provided in the above embodiments may be adaptively adjusted according to actual situations, or may be concurrently performed according to actual situations.
All or part of the steps in the methods according to the above embodiments may be implemented by a program instructing related hardware, where the program may be stored in a storage medium readable by a computer device and used to execute all or part of the steps in the methods according to the above embodiments. The computer device, for example: personal computer, server, network equipment, intelligent mobile terminal, intelligent home equipment, wearable intelligent equipment, vehicle-mounted intelligent equipment and the like; the storage medium, for example: RAM, ROM, magnetic disk, magnetic tape, optical disk, flash memory, U disk, removable hard disk, memory card, memory stick, network server storage, network cloud storage, etc.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and improvements can be made without departing from the principle of the present invention, and such modifications and improvements should also be considered within the scope of the present invention.
Claims (7)
1. A method for evaluating the life quality of the old people based on an intelligent wearing technology is characterized by comprising the following steps:
s1, determining the index for evaluating the life quality of the old, comprising: physiological function indexes, psychological function indexes and social function indexes, and acquiring composition factors and data of each index, and synchronizing all the acquired data into a database of the intelligent health platform;
s2, judging whether the data volume of each index in the database reaches a threshold value, if so, jumping to S3, otherwise, jumping to S1;
s3, carrying out non-dimensionalization treatment on all the composition factors according to the characteristics of different composition factors, carrying out forward conversion on the reverse indexes, and calculating the score of each composition factor;
s4, adding the scores of the composition factors to obtain an aged activity index score; and evaluating the life quality of the old according to the score of the activity index of the old.
2. The method for evaluating the life quality of the elderly based on the intelligent wearing technology of claim 1,
the composition factors of the physiological function index comprise: physiological function indexes which can be measured by intelligent wearing technologies such as age, gender, body pain/discomfort, chronic disease types, blood pressure, blood sugar, respiration, heart rate, eyesight, hearing and the like;
the psychological function index comprises the following components: indexes which can measure and reflect psychological functions of intelligent wearing technologies such as cognition, emotion, appetite, sleep and the like;
the composition factors of the social function include: the intelligent wearing technologies such as education level, medical insurance, occupation, income, presence or absence of spouse, social interaction, exercise level and the like can measure or obtain indexes reflecting social functions through the intelligent health platform.
3. The method for evaluating the life quality of the elderly based on the intelligent wearing technology of claim 2, wherein the data of age, sex, education level, medical insurance, occupation, income, spouse presence or absence and chronic disease category in the composition factors are directly obtained by the intelligent health platform; data of blood pressure, blood sugar, respiration, heart rate, vision, hearing, emotion, appetite, sleep, social interaction and exercise level are acquired through the intelligent wearable device and synchronized to the intelligent health platform; the data of the subjective life satisfaction of the old, the vision, the hearing and the body pain/discomfort are obtained through the intelligent terminal.
4. The method for evaluating the life quality of the elderly based on the intelligent wearing technology of claim 1, wherein in S2, the threshold is 400.
5. The method for evaluating the life quality of the elderly based on the intelligent wearing technology of claim 1, wherein S3 specifically comprises:
the composition factors comprise qualitative factors and quantitative factors, and the quantitative factors are divided into linear type factors, broken line type factors and curve type factors;
the scores of the qualitative factors convert the conversion values into numbers according to the characteristics of the composition factors;
the score of the linear factor is calculated by adopting the following formula:
wherein,
the score of the broken line type factor is calculated by adopting the following formula:
the score of the curve form factor is calculated based on the characteristics of the composition factors.
6. The method for evaluating the life quality of the elderly based on the intelligent wearing technology of claim 1, further comprising the following steps after S4: and S5, performing exploratory factor analysis on the data processed in the S3, and determining an index which has a large influence on the activity index of the elderly.
7. The method for evaluating the life quality of the elderly based on the intelligent wearing technology of claim 6, wherein S5 specifically comprises the following steps:
s501, constructing a covariance matrix by adopting a principal component analysis method and a maximum variance orthogonal rotation method:
wherein,
X1,X2,…，Xkrepresents k measurable index variables representing the number of k measurable index variables,
Rijrepresenting the correlation coefficient between k index variables;
s502, according to the calculation result of the covariance matrix, according to the following formula:
|λE-R|＝0，
calculating the eigenvalue lambdaiPrincipal component ZiThe contribution ratio of (c):and cumulative contribution rate:
s503, screening the characteristic value lambdai>1, a public factor with the cumulative contribution rate of more than 80 percent;
s504, a possible senile vitality index theoretical model is provided for each public factor;
and S505, calculating the absolute fitting index of each aging activity index theoretical model by using AMOS software and adopting a maximum likelihood estimation method: x is the number of2GFI, RMR, SRMR, RMSEA; relative fitting index: NFI, TLI, CFI; information fitting index: AI C, CAIC;
s506, judging whether the fitting index meets the evaluation standard, if so, jumping to S507, otherwise, jumping to S504;
and S507, determining an old age vitality index theoretical model corresponding to the fitting index, and analyzing indexes which have large influence on the old age vitality index according to the old age vitality index theoretical model.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2020062326A1 (en) * | 2018-09-30 | 2020-04-02 | 上海笛乐护斯健康科技有限公司 | Smart health management and life safety insurance system, and implementation method therefor |
| CN112826186A (en) * | 2021-01-11 | 2021-05-25 | 成都体育学院 | Intelligent bracelet |
| CN116109456A (en) * | 2023-04-03 | 2023-05-12 | 成都大学 | Comprehensive evaluation method and system for intelligent education, electronic equipment and storage medium |
| CN118016302A (en) * | 2024-04-07 | 2024-05-10 | 北京健康有益科技有限公司 | Health risk assessment method and system for multi-source data input |
-
2016
- 2016-11-18 CN CN201611019746.2A patent/CN106777872A/en active Pending
Non-Patent Citations (2)
| Title |
|---|
| 姜晶梅: "层次分析法与老年人生命质量的综合评价", 《中国优秀博硕士学位论文全文数据库（博士）医药卫生科技辑》 * |
| 李跃平等: "验证性因子分析在量表结构效度考核中作用", 《中国公共卫生》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2020062326A1 (en) * | 2018-09-30 | 2020-04-02 | 上海笛乐护斯健康科技有限公司 | Smart health management and life safety insurance system, and implementation method therefor |
| CN112826186A (en) * | 2021-01-11 | 2021-05-25 | 成都体育学院 | Intelligent bracelet |
| CN116109456A (en) * | 2023-04-03 | 2023-05-12 | 成都大学 | Comprehensive evaluation method and system for intelligent education, electronic equipment and storage medium |
| CN116109456B (en) * | 2023-04-03 | 2023-07-28 | 成都大学 | Comprehensive evaluation method and system for intelligent education, electronic equipment and storage medium |
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