Gesture Recognition Via Flexible Capacitive Touch Electrodes

Abstract

A novel wearable device for gesture recognition was developed and tested on five subjects. The low-cost, wireless wearable device was engineered with a set of seven flexible capacitive touch electrodes sewn into an armband to be worn on the forearm between the wrist and elbow. These capacitive touch electrodes were interfaced with a microcontroller and bluetooth transceiver for measurement and transmission. As different gestures are made, flexing muscles beneath the skin affect the capacitance measured on these seven electrodes. A set of 32 gestures were tested including the 16 grasps in the Cutkosky Grasp Taxonomy and 16 basic finger and wrist motions. Several classification algorithms were tested on this data. Using a Random Forest (RF) algorithm to classify the training data, an average gesture recognition accuracy of 95.6 ± 0.06% was achieved across all five subjects individually.