CN107273666B - Human health data comprehensive analysis system - Google Patents
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- CN107273666B CN107273666B CN201710386321.3A CN201710386321A CN107273666B CN 107273666 B CN107273666 B CN 107273666B CN 201710386321 A CN201710386321 A CN 201710386321A CN 107273666 B CN107273666 B CN 107273666B
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Abstract
The invention discloses a human health data comprehensive analysis system, which comprises: the system comprises a user information module, a health data module, a user label module, an equipment information acquisition module and a health analysis module; the user information module is used for storing the information of all users through a data table; the equipment information acquisition module is used for acquiring health data from the health equipment through the Bluetooth interface and sending the measured health data to the server through a post request; the health data module is used for storing all data information acquired by the health equipment through a data table; the health analysis module is used for making a health analysis report according to the data information stored by the health data module and the user information stored by the user information module; and the user tag module is used for setting a user tag according to the content published by the user in the health forum and pushing the article to the user according to the user tag.
Description
Technical Field
The invention relates to an internet health analysis technology, in particular to a human health data comprehensive analysis system.
Background
Medical problems in the current society are paid more and more attention, and more products related to medical health are introduced, wherein the products acquire personal health data through health acquisition equipment and obtain conclusions after analyzing the acquired data in the background. However, many medical health products are developed only for one or several health collecting devices, and thus have limitations in the kinds of health data acquired. Meanwhile, the general medical health products have single functions, and besides the function of analyzing health data, the functions of mutual communication among users are lacked.
Disclosure of Invention
The invention aims to solve the technical problem of providing a human health data comprehensive analysis system aiming at the defects in the prior art.
The technical scheme adopted by the invention for solving the technical problems is as follows: a system for integrated analysis of human health data, comprising: the system comprises a user information module, a health data module, a user label module, an equipment information acquisition module and a health analysis module;
the user information module is used for storing information of all users through a data table, and the storage format is { user id, mobile phone number, account number, nickname, gender, password, height, weight, age, address, user type, bust, waistline, hip circumference, whether the user is a common user, whether the user is a pregnant woman, tag 1, tag 2, tag 3, tag 4, tag 5, device 1, device 2, device 3, device 4, device 5, device 6, device 7, device 8, device 9, device 10, tag 1 weight, tag 2 weight, tag 3 weight, tag 4 weight, tag 5 weight };
the equipment information acquisition module is used for acquiring health data from the health equipment through the Bluetooth interface and sending the measured health data to the server through a post request;
the health data module is used for storing all data information acquired by the health equipment through a data table; the storage format is { data id, user id, device type, walking number, heart rate value, time to sleep, light sleep time, deep sleep time, total sleep time, height value, weight value, height of father, height of mother, recording date, score value, temperature value, systolic pressure value, diastolic pressure value, blood pressure median, blood oxygen value, blood fat value, menstruation start date, menstruation end date };
the health analysis module is used for making a health analysis report according to the data information stored by the health data module and the user information stored by the user information module;
and the user tag module is used for setting a user tag according to the content published by the user in the health forum and pushing the article to the user according to the user tag.
According to the scheme, the specific steps of setting the user tag according to the content published by the user in the health forum are as follows:
1) when a user publishes a post in a forum, the user is allowed to select a primary topic label preset in the forum by default, and after the post and the primary topic label are obtained, a corresponding primary topic LDA model is used for extracting a topic phrase;
the primary topic LDA model is a plurality of primary topic LDA models established by using an LDA topic model training document set; the establishing steps are as follows:
determining the number of topics according to the size of the minimum set through the artificial tag information of the original data of the sub-topics of the topics in the forum;
training a topic model of Gensim by using a document set in a Chinese language database aiming at each sub-topic; the Chinese language database is established by using crawlers to acquire data of sub-topics of the topics in the selected forum;
according to the training result of the topic model, taking high-proportion words with the preset number of the composition of each topic as topic keywords of the topic;
2) and updating the label of the user according to the extracted subject phrase.
According to the scheme, the article is pushed to the user according to the user label, and related contents are screened in the forum for recommendation according to the label of the user and the sequence that the label word weight is reduced in sequence.
According to the scheme, the health equipment comprises a health device and a mio bracelet.
According to the scheme, the health data comprise exercise steps, heart rate, sleep time, total sleep time, deep sleep time, shallow sleep time, weight, height of father, height of mother, body temperature, diastolic pressure, systolic pressure, median blood pressure, blood oxygen, blood fat, blood sugar and start and end date of menstruation.
According to the scheme, the health analysis report in the health analysis module comprises user health scores and character comments;
the health analysis report is generated as follows:
1) comparing the data with corresponding normal human body standard values according to blood pressure, blood oxygen and body temperature data in the data information stored by the health data module and gender, age, height, weight and user type information in the user information, scoring and adding corresponding comments according to the score;
2) analyzing the exercise step number and the sleep quantity data, grading the exercise quantity and the sleep quantity of the current day by referring to the normal exercise quantity required by the health of the human body and the sleep required by each age group, and returning a preset text comment corresponding to the grading;
3) respectively using a CMH method and an FPH method, predicting the heights of boys and girls by using the heights of parents, and returning the height prediction conditions of the children of the user in a text description mode;
4) calculating the hypertension occurrence risk of the user in the next 15 years according to a method described in a thesis of predicting 15-year hypertension occurrence risk of people 35-64 years old in China, through factors of the user's uploaded age, systolic pressure, diastolic pressure, BMI and family history of hypertension;
5) calculating the probability of heart disease of Chinese people by referring to a China-PAR model according to data such as gender, height, weight, age, blood pressure and the like uploaded by a user, returning a health score, calculating the probability of heart disease of the user, and performing character analysis;
6) calculating the BMI index of the user according to the gender, height, weight and age data uploaded by the user, and returning a health score and character analysis;
7) and combining the analysis information into a health analysis report.
The invention has the following beneficial effects: the invention provides a human health comprehensive analysis system which can be compatible with a plurality of different data acquisition devices and theoretically acquire all data acquired by human physical ability, so that a more accurate health analysis conclusion can be obtained according to more comprehensive health data and provided for a forum platform of a user, and the user can acquire more health information concerned by the user.
Drawings
The invention will be further described with reference to the accompanying drawings and examples, in which:
FIG. 1 is a general flow diagram of the present invention;
FIG. 2 is a schematic diagram of a data flow for use with the system of the present invention;
FIG. 3 is a diagram of a database user data table structure according to the present invention;
FIG. 4 is a diagram of a database data record table structure according to the present invention;
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 with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, a system for comprehensively analyzing human health data includes: the system comprises a user information module, a health data module, a user label module, an equipment information acquisition module and a health analysis module;
the user information module is used for storing information of all users through a data table, as shown in fig. 3, the storage format is { user id, mobile phone number, account number, nickname, gender, password, height, weight, age, address, user type, chest circumference, waist circumference, hip circumference, whether the user is a common user or not, whether the user is a pregnant woman or not, tag 1, tag 2, tag 3, tag 4, tag 5, device 1, device 2, device 3, device 4, device 5, device 6, device 7, device 8, device 9, device 10, tag 1 weight, tag 2 weight, tag 3 weight, tag 4 weight, tag 5 weight };
the equipment information acquisition module is used for acquiring health data from the health equipment through the Bluetooth interface and transmitting the acquired health data to the server through a post request;
as shown in fig. 2, the user connects the android client to the mio bracelet detection device by using bluetooth 4.0 and ANF +, and obtains health data stored in the bracelet, including an average heart rate, a maximum heart rate, statistics of exercise steps and a running speed detected in real time during exercise; and acquiring sleep data of the user during sleeping, wherein the sleep data comprise sleep time and sleep time data, deep sleep time and previous sleep time in the sleeping process, and real-time heart rate data. Utilize bluetooth 4.0 to be connected healthy precious health data measuring equipment of family and key with the tall and erect application of ann, use blood pressure sleeve area test more accurate blood pressure data, use oxyhemoglobin saturation probe clamp to test oxyhemoglobin saturation on hand, available body temperature probe test body temperature uses the heart point wire to test electrocardio data, and check out test data transmission gives the tall and erect client of ann with check out test equipment.
The health data module is used for storing all data information acquired by the health equipment through a data table; as shown in fig. 4, the storage format is { data id, user id, device type, walking number, heart rate value, time to sleep, length of light sleep, length of deep sleep, total length of sleep, height value, weight value, height of father, height of mother, recording date, score value, temperature value, systolic blood pressure value, diastolic blood pressure value, blood pressure median, blood oxygen value, blood lipid value, date of onset of menstruation, date of end of menstruation };
the health analysis module is used for making a health analysis report according to the data information stored by the health data module and the user information stored by the user information module;
and the background analyzes the health record of the user after obtaining the health record and returns an analysis result. The specific analysis result specifically comprises a user health score and a text comment. The specific health analysis method is as follows: 1. uploading blood pressure, blood oxygen and body temperature data by a user, comparing the data with a normal human body standard value by a background, scoring and adding comments of hypertension, hypotension and the like; 2: analyzing the exercise step number and the sleep quantity, referring to the normal exercise quantity required by the health of a human body and the sleep required by each age group, grading the exercise quantity and the sleep quantity on the same day, and returning to text comment; 3: respectively using a CMH method and an FPH method, predicting the heights of boys and girls by using the heights of parents, and returning the height prediction conditions of the children of the user in a text description mode; 4: according to a reference paper '15-year hypertension occurrence risk prediction research of people 35-64 years old in China', the 15-year hypertension occurrence risk of a user is calculated through factors of the age, systolic pressure, diastolic pressure, BMI and family history of hypertension uploaded by the user; 5: calculating the probability of heart disease of Chinese people by referring to a China-PAR model according to data such as gender, height, weight, age, blood pressure and the like uploaded by a user, returning a health score, calculating the probability of heart disease of the user, and performing character analysis; 6: calculating the BMI index of the user according to the gender, height, weight and age data uploaded by the user, and returning a health score and character analysis;
and the user tag module is used for setting a user tag according to the content published by the user in the health forum and pushing the article to the user according to the user tag.
The specific steps of setting the user tag according to the content published by the user in the health forum are as follows:
1) when a user publishes a post in a forum, the user is allowed to select a primary topic label preset in the forum by default, and after the post and the primary topic label are obtained, a corresponding primary topic LDA model is used for extracting a topic phrase;
the primary topic LDA model is a plurality of primary topic LDA models established by using an LDA topic model training document set; the establishing steps are as follows:
determining the number of topics according to the size of the minimum set through the artificial tag information of the original data of the sub-topics of the topics in the forum;
training a topic model of Gensim by using a document set in a Chinese language database aiming at each sub-topic; the Chinese language database is established by using crawlers to acquire data of sub-topics of the topics in the selected forum;
according to the training result of the topic model, taking high-proportion words with the preset number of the composition of each topic as topic keywords of the topic;
2) and updating the label of the user according to the extracted subject phrase.
The article is pushed to the user according to the user label, and related contents are screened in the forum for recommendation according to the label of the user and the sequence that the label word weight is reduced in sequence.
It will be understood that modifications and variations can be made by persons skilled in the art in light of the above teachings and all such modifications and variations are intended to be included within the scope of the invention as defined in the appended claims.
Claims (3)
1. A system for integrated analysis of human health data, comprising: the system comprises a user information module, a health data module, a user label module, an equipment information acquisition module and a health analysis module;
the user information module is used for storing information of all users through a data table, and the storage format is { user id, mobile phone number, account number, nickname, gender, password, height, weight, age, address, user type, bust, waistline, hip circumference, whether the user is a common user, whether the user is a pregnant woman, tag 1, tag 2, tag 3, tag 4, tag 5, device 1, device 2, device 3, device 4, device 5, device 6, device 7, device 8, device 9, device 10, tag 1 weight, tag 2 weight, tag 3 weight, tag 4 weight, tag 5 weight };
the equipment information acquisition module is used for acquiring health data from the health equipment through the Bluetooth interface and sending the measured health data to the server through a post request;
the health data module is used for storing all data information acquired by the health equipment through a data table; the storage format is { data id, user id, device type, exercise step number, heart rate value, time to fall asleep, light sleep time, deep sleep time, total sleep time, height value, weight value, father height, mother's height, recording date, score value, temperature value, systolic pressure value, diastolic pressure value, blood pressure median, blood oxygen value, blood lipid value, menstruation start date, menstruation end date };
the health analysis module is used for making a health analysis report according to the data information stored by the health data module and the user information stored by the user information module;
the user tag module is used for setting a user tag according to the content published by the user in the health forum and pushing an article to the user according to the user tag;
the specific steps of setting the user tag according to the content published by the user in the health forum are as follows:
1) when a user publishes a post in a forum, the user is allowed to select a primary topic label preset in the forum by default, and after the post and the primary topic label are obtained, a corresponding primary topic LDA model is used for extracting a topic phrase;
the primary topic LDA model is a plurality of primary topic LDA models established by using an LDA topic model training document set; the establishing steps are as follows:
determining the number of topics according to the size of the minimum set through the artificial tag information of the original data of the sub-topics of the topics in the forum;
training a topic model of Gensim by using a document set in a Chinese language database aiming at each sub-topic; the Chinese language database is established by using crawlers to acquire data of sub-topics of the topics in the selected forum;
according to the training result of the topic model, taking high-proportion words with the preset number of the composition of each topic as topic keywords of the topic;
2) and updating the label of the user according to the extracted subject phrase.
2. The system of claim 1, wherein the health data comprises exercise steps, heart rate, time to sleep, total length of sleep, length of deep sleep, length of shallow sleep, weight, height of the father, height of the mother, body temperature, diastolic pressure, systolic pressure, median blood pressure, blood oxygen, blood lipids, blood glucose, date of onset of menstruation and date of end of menstruation.
3. The system for comprehensively analyzing human health data according to claim 1, wherein the health analysis report in the health analysis module comprises a user health score and a text comment;
the health analysis report is generated as follows:
1) comparing the data with corresponding normal human body standard values according to blood pressure, blood oxygen and body temperature data in the data information stored by the health data module and gender, age, height, weight and user type information in the user information, scoring and adding corresponding comments according to the score;
2) analyzing the exercise step number and the sleep quantity data, grading the exercise quantity and the sleep quantity of the current day by referring to the normal exercise quantity required by the health of the human body and the sleep required by each age group, and returning a preset text comment corresponding to the grading;
3) respectively using a CMH method and an FPH method, predicting the heights of boys and girls by using the heights of parents, and returning the height prediction conditions of the children of the user in a text description mode;
4) calculating the hypertension occurrence risk of the user in the next 15 years according to a method described in a thesis of predicting 15-year hypertension occurrence risk of people 35-64 years old in China, through factors of the user's uploaded age, systolic pressure, diastolic pressure, BMI and family history of hypertension;
5) calculating the probability of suffering from heart diseases of Chinese people by referring to a China-PAR model according to the gender, height, weight, age and blood pressure data uploaded by the user, returning a health score, the probability of suffering from heart diseases of the user and character analysis;
6) calculating the BMI index of the user according to the gender, height, weight and age data uploaded by the user, and returning a health score and character analysis;
7) and combining the analysis information into a health analysis report.
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| CN108542427A (en) * | 2018-04-08 | 2018-09-18 | 深圳市贝斯曼精密仪器有限公司 | A kind of wearable ultrasonic doppler blood flow detector and detection method |
| CN111428742B (en) * | 2018-12-24 | 2023-12-19 | 有品国际科技(深圳)有限责任公司 | Human health measurement method, device, computer equipment and storage medium |
| CN110222204A (en) * | 2019-06-21 | 2019-09-10 | 天津联恩教育科技有限公司 | Children's early education behavior observation system |
| CN110428901B (en) * | 2019-07-19 | 2022-02-11 | 中国医学科学院阜外医院 | Cerebral apoplexy attack risk prediction system and application |
| CN110517778A (en) * | 2019-08-29 | 2019-11-29 | 四川长虹电器股份有限公司 | A kind of method for weight management of Intelligent weight scale |
| CN114974580B (en) * | 2022-04-22 | 2023-05-23 | 上海铂桐医疗科技有限公司 | Fracture risk detection data processing method and system |
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