Gesture Recognition: A Comprehensive Approach Using Electrical Impedance Tomography for Whole-Arm Monitoring

This study introduces an EIT -based gesture recognition system focusing on the entire arm, including hand movements. Utilizing a 16-electrode system and the Gauss-Newton method, we conducted experiments with six participants, testing various gestures at frequencies of 1 kHz, 10 kHz, and 100 kHz. The introduced Similarity Evaluation Index (SEI) identified 10 kHz as a potentially optimal testing frequency, exhibiting an 11 % difference in relative conductivity. Repeated measurements demonstrated system stability, while individual variations underscored the complexity influenced by behavioral habits and physiology. Future endeavors aim to refine sensitivity, expand the gesture repertoire, and explore practical applications, positioning this work at the forefront of human-technology interaction research.