On Optimizing Electrode Configuration for Wrist-Worn sEMG-Based Thumb Gesture Recognition

2026-04-06

AI Summary

This study investigates the impact of electrode configuration on gesture decoding performance when using surface electromyography (sEMG) from the wrist for thumb gesture recognition—a factor not yet well understood. The authors systematically compare high-density and low-density sEMG setups, examining electrode placement, referencing schemes, channel count, and spatial density. Results demonstrate that electrode placement over the extensor side significantly outperforms the flexor side (HD accuracy: 0.871 vs. 0.821), unipolar referencing yields better performance than bipolar, and a 15-channel unipolar configuration achieves an accuracy of 0.885. Further increases in channel count yield diminishing returns. The findings highlight the necessity of balancing coverage and compactness in electrode layout and underscore that thoughtful configuration design is more critical than simply increasing electrode number, offering practical optimization strategies for wearable wrist sEMG systems.

Abstract

Thumb gestures provide an effective and unobtrusive input modality for wearable and always-available human-machine interaction. Wrist-worn surface electromyography (sEMG) has emerged as a promising approach for compact and wearable human-machine interfaces. However, compared to forearm sEMG, the impact of electrode configuration on wrist-based decoding performance remains understudied. We systematically investigated electrode configuration strategies for wrist-based thumb-movement recognition using high-density (HD) and low-density (LD) sEMG measurement systems. We considered factors such as muscle region, reference scheme, channel count, and spatial density of the electrode. Experimental results show that 1) extensor-side electrodes outperform flexor-side electrodes (HD: 0.871 vs. 0.821; LD: 0.769 vs. 0.705); 2) monopolar recordings consistently outperform bipolar configurations (15 channel with HD monopolar vs. LD bipolar: 0.885 vs. 0.823); and 3) increasing channel count enhances performance, but exhibits diminishing returns. We further show that electrode spatial distribution introduces a trade-off between spatial coverage and compactness. The findings suggest that the effectiveness of wrist-worn sEMG systems depends less on the deployment of a large number of electrodes in a broad sensing area and more on the optimization of electrode placement and the referencing scheme. This work provides practical guidelines for developing efficient wrist-worn sEMG-based gesture recognition systems.

Problem

• electrode configuration
• wrist-worn sEMG
• thumb gesture recognition
• surface electromyography
• gesture decoding

Innovation

• electrode configuration
• wrist-worn sEMG
• thumb gesture recognition
• monopolar vs. bipolar
• spatial density