Gesture Recognition on Textile-Based Pressure Sensor Array

Wearable technologies are in pursuit of designing portable devices worn by people. In this paper, gesture recognition on a sleeve having a capacitive textile-based pressure sensor array has been developed. Machine learning models are generated to recognize a set of gestures by accumulating capacitance values read from a sensor array during the execution of gestures. The performance of the gesture recognition system is evaluated in the experiments conducted with human test subjects. Real-time gesture prediction is achieved using the trained model. The performed gestures and predicted data are collected and analyzed, resulting in accuracies up to 86'.