Fully integrated sweat parameter monitoring and analyzing system

Abstract

The invention relates to a fully integrated sweat parameter monitoring and analyzing system which comprises a background analysis system and an acquisition terminal, wherein the acquisition terminal comprises a power supply module, a master control unit (MCU), a communication module, a sweat extraction insulation module, a display screen, a clock control module, keys, a Jlink interface, a glucosesensor, a sodium ion sensor, a potassium ion sensor and a temperature sensor; and the glucose sensor, the sodium ion sensor, the potassium ion sensor and the temperature sensor are simultaneously andrespectively in bidirectional electrical connection with the sweat extraction insulation module. The fully integrated sweat parameter monitoring and analyzing system disclosed by the invention has theadvantages that sweat is noninvasively detected in real time so as to acquire health data, the data is displayed on the acquisition terminal and transmitted to the background analysis system for performing big data statistics and analysis, and clinical basis is provided for influences of various parameters in different human body 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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