Towards Next-Generation Myoelectric Prostheses: 3D-Printed Electrode Arrays for Gesture Recognition

This study presents the design, fabrication, and evaluation of a 12-channel 3D-printed electrode array for electromyography (EMG) applications. The array consists of conductive electrodes embedded within a flexible, non-conductive frame, designed to conform to the forearm and ensure uniform contact. Fabricated using dual-material 3D printing, thermoplastic polyurethane (TPU) was used for its flexibility, while Protopasta^® Composite PLA provided conductivity. The array was evaluated through controlled experiments with 10 participants performing six hand gestures. A simple linear discriminant analysis model using wavelet energy was employed to classify the recorded signals. Hand gesture classification average accuracy of (91.32 ± 7.23)% was obtained, demonstrating reliable motion recognition. These results highlight the array's potential as a cost-effective, customizable, and high-performance solution for wearable myoelectric systems.