Centimeter Differences in Wrist Electrode Placement Significantly Impact Myoelectric Performance

Area of Science:

• Biomedical Engineering
• Human-Computer Interaction
• Neuroscience

Background:

• Electromyography (EMG) is crucial for classifying hand gestures and motions, widely used in prosthetics and orthotics.
• Consumer applications increasingly favor wrist-worn EMG devices for a more socially acceptable form factor.
• Wrist-worn EMG systems face challenges due to fewer electrodes and variable placement relative to muscle anatomy.

Purpose of the Study:

• To investigate how electrode location along the wrist affects EMG signal quality and myoelectric control performance.
• To compare EMG recording quality and myoelectric control across different wrist electrode positions (distal, central, proximal).

Main Methods:

• Recorded EMG signals using electrode arrays placed at the wrist and forearm.
• Compared myoelectric control performance across three distinct electrode regions on the wrist.
• Utilized k-Nearest Neighbors (k-NN) model for classification accuracy assessment.
• Analyzed EMG information content using principal component analysis and channel selection methods.

Main Results:

• A proximal shift of 4.3 cm on the wrist significantly improved EMG information content and myoelectric performance.
• Classification accuracy with a k-NN model increased from 79.3% (distal) to 83.7% (proximal) wrist positions.
• EMG from the proximal wrist region demonstrated higher information content, evidenced by greater variance in principal components and more frequently selected channels.

Conclusions:

• Spatial electrode positioning on the wrist critically impacts myoelectric control, unlike traditional forearm recordings.
• Findings inform the design of future wrist-worn EMG devices for enhanced control.
• Improved myoelectric control can benefit applications such as partial hand prostheses, orthoses, and augmented/virtual reality systems.