Quantitative Muscle Fatigue Estimation with High SNR Flexible Skin Electrode

Area of Science:

• Biomedical Engineering
• Neuroscience
• Materials Science

Background:

• Surface electromyography (sEMG) is crucial for diagnosing neuromuscular abnormalities.
• High signal-to-noise ratio (SNR) is essential for accurate sEMG analysis.
• Traditional Ag/AgCl electrodes have limitations for long-term monitoring.

Purpose of the Study:

• To enhance the SNR of bioelectrical signals for improved sEMG measurements.
• To develop a flexible skin-electrode with increased surface area using noble metals.
• To propose a novel algorithm for real-time muscle fatigue estimation.

Main Methods:

• Electroplating a flexible noble metal skin-electrode to increase its surface area by 1.38 times.
• Measuring and comparing the SNR of sEMG signals before and after electrode modification.
• Developing and validating a muscle fatigue estimation algorithm using high-SNR sEMG data.

Main Results:

• The electroplating process successfully increased the electrode surface area.
• The modified electrode achieved a 1.63 times improvement in sEMG signal-to-noise ratio (SNR).
• High-SNR sEMG signals facilitated the development of a reliable real-time muscle fatigue algorithm.

Conclusions:

• Increased noble metal electrode surface area significantly improves sEMG SNR.
• Enhanced SNR enables more accurate real-time monitoring of muscle conditions.
• The proposed algorithm offers a promising approach for clinical muscle fatigue assessment.