Feasibility of Wrist-Worn, Real-Time Hand, and Surface Gesture Recognition via sEMG and IMU Sensing

Abstract

While most wearable gesture recognition approaches focus on the forearm or fingers, the wrist may be a more suitable location for practical use. We present the design and validation of a real-time gesture recognition wristband based on surface electromyography and inertial measurement unit sensing fusion, which can recognize 8 air gestures and 4 surface gestures with 2 distinct force levels. Ten healthy subjects performed an initial gesture recognition experiment, followed by a second experiment 1 h later and a third experiment 1 day later. Classification accuracies for the initial experiment were 92.6% and 88.8% for air and surface gestures, respectively, and there were no changes in accuracy results during testing 1 h. and 1 day later ( $p$ $>$ 0.05). These results demonstrate the feasibility of wrist-based gesture recognition paving the way for potential future integration in to a smart watch or other wrist-worn wearable for intuitive human computer interaction.