Health protection robot system and data processing method thereof

Abstract

The invention discloses a health protection robot system and a data processing method thereof, and relates to the field of medical care, in particular to an intelligent health protection system which is used for integrating fragmented health data so as to realize scientific user health behavior intervention. The invention aims to provide a health protection system which has the advantages of being simple in structure, low in cost and convenient in operation, integrates the fragmented health data, carries out intelligent analysis and carries out intervention on the user health behavior by the system. The health protection robot system comprises an acquisition module, a server and a terminal, wherein the acquisition module is used for collecting the health and medical care data of a user; the server carries out comparison, analysis and model operation through the uploaded health and medical care data, generates a health data summarization and evaluation report and a health intervention scheme, and provides control and support for the operation of a virtual robot; and the terminal is used for a registered user to carry out login, causes the registered user to receive the health data in the acquisition module and is provided with a display module used for displaying the health data and system functions.

Description

Technical field [0001] The present invention relates to an objective health data processing system and a data processing method, and in particular to a health data processing system, data processing method, health management and intervention method for processing fragmented, fractured and correlated health data. Background technique [0002] In existing personal health management, objective sign status data such as body weight, exercise consumption, blood pressure, blood sugar, heart rate, sleep quality, and medical process data are usually completed by multiple independent closed-loop acquisition processes, and random or independent data For output processing, existing technologies cannot integrate these fragmented data based on cohesive conditions such as time correlation and data inherent correlation. In this way, it is difficult to establish intercommunication, association and verification between data, which brings inconvenience to the judgment and management of the use...

AI Technical Summary

Problems solved by technology

[0002] In existing personal health management, objective sign status data such as body weight, exercise consumption, blood pressure, blood sugar, heart rate, sleep quality, and medical process data are usually completed by multiple independent closed-loop acquisition processes, and random or independent data Output processing, the existing technology cannot integrate these fragmented data based on cohesive conditions such as time correlation and data intrinsic correlation

In this way, it is difficult to establish intercommunication, association and verification between data, which brings inconvenience to the judgment and management of user health status

It is also impossible to aggregate the data into one place for fusion, making it difficult for doctors to accurately judge the patient's physical condition based on the obtained data

For example, if the user's weight is beyond the normal range, based on this single weight data, suggestions for controlling calorie intake and increasing exercise may be given, which may ignore that the user may have continued to lose weight, or suffer from wasting diseases. cause the judgment may not be correct

At the same time, personal life has been out of the scope of medical monitoring for a long time. How to scientifically, systematically and continuously guide and intervene in personal health-related behaviors also lacks effective technical means

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