Fully-integrated sweat parameter monitoring and analysis system

Abstract

The invention relates to a fully-integrated sweat parameter monitoring and analysis system. The fully-integrated sweat parameter monitoring and analysis system includes a background analysis system and a collection terminal, wherein the collection terminal comprises a power supply module, a main control board MCU, a communication module, a sweat extraction insulation module, a display screen, a clock control module, a button, a Jlink interface, a glucose sensor, a sodium ion sensor, a potassium ion sensor and a temperature sensor; the glucose sensor, the sodium ion sensor, the potassium ion sensor and the temperature sensor are electrically connected to the sweat extraction insulation module at the same time. The fully-integrated sweat parameter monitoring and analysis system has the advantages of obtaining health data by non-invasive real-time detection of sweat, displaying the health data on the collection terminal, and sending the health data to the background analysis system for big data statistics and analysis, and providing clinical references for the influence of various parameters in different human environments.

Description

technical field [0001] The invention relates to the fields of smart wear, health detection, and big data analysis, in particular to a fully integrated sweat parameter monitoring and analysis system. Background technique [0002] With the popularity of wearable products and people's requirements for health monitoring, in addition to general physical activity and vital signs of health monitoring can not meet people's needs, especially the monitoring of a certain index for patients with a certain type of disease: 1. Chlorine Departure: The concentration of chloride ions in sweat is an important method for diagnosing cystic fibrosis. 2. Sodium ion: It can be used to monitor the dehydration status of the human body. 3. Glucose: Can be used to monitor blood sugar concentration. Sweat extraction of physiological parameters is a non-invasive detection method, which makes it possible to obtain detection data in real time, so as to conduct large-scale clinical research and big data ...

AI Technical Summary

Problems solved by technology

[0003] However, the existing technology has the following shortcomings: 1. General wearable products only involve physical activities and vital signs, and cannot obtain physiological health monitoring

2. Sweat is not used as a sample to extract physiological parameters, but body fluids or blood are used for testing, which cannot be non-invasive and non-invasive, because it cannot be used on a large scale by the general public, because it cannot be analyzed by big data

3. The timeliness experience is not good: because intrusive detection generally requires background instrument analysis, it is impossible to provide real-time feedback data to the monitoring object

4. There is no real-time correction. Generally, the data of human body sensors is inaccurate and has a greater impact on environmental factors. For example, the measured value of the glucose sensor has a greater relationship with temperature

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