Soft Wrist-Worn Multi-Functional Sensor Array for Real-Time Hand Gesture Recognition

Soft electronics have been widely applied to wearable electronics, hand gesture detection and human robot interaction (HR I). Soft wrist-worn sensor system (SWSS) with electromyography (EMG), strain/pressure sensing abilities has been created for continuous hand gesture recognition, which includes multi-source data sensing, data collection and process, and wireless communication. SWSS is conformal contact with skin surface as the softness of SWSS, and it would improve the wearability with the wrist during long-term hand gesture monitoring. Linear discriminant analysis (LDA) and support vector machines (SVM) algorithms are applied to hand gesture recognition with average accuracy 83.67%, 86.8% for Group #1 (wrist flexion (WF), wrist extension (WE), finger flexion (FF), finger extension (FE), radial deviation (RD), and ulnar deviation (UD)) and 84.71%, 88.53% for Group #2 (sign language 0-9 digits), respectively. It is found that the recognition accuracy has just a little decreased during the long-term hand gesture detection at different sessions (at initial time, one day after, three days after and seven days after). This paper demonstrated the feasibility of gesture recognition via SWSS on wrist, and it could be integrated into wrist-worn electronic system for human robot interaction.

Automated summary

Soft electronics have been widely used in wearable devices, hand gesture recognition, and human robot interaction. This study introduces a soft wrist-worn sensor system (SWSS) with electromyography (EMG) and strain/pressure sensing capabilities for continuous hand gesture recognition. The results show that SWSS has good wearability and high accuracy in hand gesture recognition, even during long-term monitoring.