Integrating Wearable Textiles Sensors and IoT for Continuous sEMG Monitoring

Area of Science:

• Biomedical Engineering
• Wearable Technology
• Signal Processing

Background:

• Surface electromyography (sEMG) is crucial for assessing muscle function in clinical, research, and sports settings.
• Continuous sEMG monitoring is desirable for tracking muscle activity and fatigue.
• Existing methods often rely on cumbersome gelled electrodes.

Purpose of the Study:

• To develop an integrated biomedical monitoring system using a wearable textile sensor for continuous sEMG.
• To enable telemetric assessment of muscle activities and fatigue.
• To validate the performance of the developed smart textile electrode against conventional methods.

Main Methods:

• Developed a smart sleeve bandage with an embroidered textile electrode for sEMG signal acquisition.
• Utilized an Internet of Things (IoT) approach with a Myoware sensor and ESP8266 microcontroller for wireless data transmission.
• Implemented a webserver-cum-database on a mobile phone or PC for data processing and visualization.
• Compared sEMG signals from biceps, triceps, and tibialis muscles using the textile electrode and gelled electrodes.
• Performed principal component analysis (PCA) and one-way MANOVA on time and frequency domain features.

Main Results:

• The developed textile electrode integrated with IoT successfully measured sEMG signals.
• Signal quality was found to be comparable to conventional gelled electrode methods.
• Quantitative analysis (RMS, ARV) showed consistent sEMG values across muscle and electrode types.
• Statistical analysis (PCA, MANOVA) indicated no significant differences between muscle types or electrode types.

Conclusions:

• The developed wearable textile sensor system offers a viable and effective method for continuous sEMG monitoring.
• The IoT-based approach facilitates telemetric assessment of muscle activity and fatigue.
• The smart textile electrode demonstrates comparable performance to traditional gelled electrodes, paving the way for more comfortable and accessible muscle monitoring.