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Updated: Jul 19, 2025

A Detailed Protocol for Perspiration Monitoring Using a Novel, Small, Wireless Device

A Detailed Protocol for Perspiration Monitoring Using a Novel, Small, Wireless Device

Published on: November 24, 2016

Machine learning-assisted flexible wearable device for tyrosine detection.

Qiwen Bao¹, Gang Li¹, Wenbo Cheng²

¹School of Precision Instrument and Optoelectronic Engineering, The State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University 92 Weijin Road Tianjin 300072 China linling@tju.edu.cn.

|August 10, 2023

Summary

This summary is machine-generated.

This study introduces a smart, portable electrochemical biosensor for detecting tyrosine (Tyr). Machine learning enhances accuracy by integrating sensor data with environmental factors like pH and temperature for improved disease diagnosis.

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Area of Science:

Electrochemistry
Biosensors
Machine Learning
Analytical Chemistry

Background:

Early diagnosis of pathological markers is crucial for disease control.
Current clinical methods are often expensive and complex.
There is a need for simpler, rapid, and intelligent analytical techniques.

Purpose of the Study:

To develop a smart, portable electrochemical biosensor for tyrosine detection.
To utilize machine learning for enhanced analytical accuracy.
To integrate a flexible wearable device with a novel electrode material.

Main Methods:

Fabrication of a carbon black-graphene oxide conjugate polymer (CB-GO/CP) electrode.
Development of a flexible wearable device for portable detection.
Application of artificial neural network (ANN) and support vector machines (SVM) models.
Data collection in artificial urine, incorporating pH and temperature variations.

Main Results:

The proposed CB-GO/CP electrode demonstrates effective electrochemical sensing capabilities.
Machine learning models accurately predicted tyrosine concentration.
Integration of external factors (pH, temperature) significantly improved model prediction accuracy.

Conclusions:

Machine learning-assisted electrochemical biosensors offer a promising approach for smart, portable diagnostics.
The developed system provides a simpler, more efficient, and intelligent alternative to traditional methods.
This technology has potential applications in early disease diagnosis and monitoring.