Wearable Soft Sensing Band with Stretchable Sensors for Torque Estimation and Hand Gesture Recognition

Abstract

This paper presents a wearable soft sensing band with stretchable sensors to monitorcle activity by estimating muscle volume changes. Unlike conventional surface electromyography (sEMG) sensing techniques, which require excessive pressure or adhesive electrodes, the proposed sensing method allows muscle volume variations to be detected simply by placing the device on the skin without additional pressure or adhesives. The band was evaluated in isometric-static and isometric-varying torque estimation tasks, demonstrating superior accuracy to sEMG, with a relative torque to maximum torque estimation error of less than 11.5%. In isometric-varying conditions, relative torque was estimated with an average error of 10.1% at frequencies of 0.1 Hz, 0.2 Hz and 0.5 Hz. Furthermore, the band achieved a classification accuracy of 92.9% in recognizing ten distinct hand gestures, highlighting its capability to differentiate between multiple muscle activations. The lightweight and flexible design addresses limitations of sEMG, such as signal noise, skin irritation, and complex calibration. Experimental results validate the potential of the proposed sensing method for applications in muscle activity monitoring across healthcare, rehabilitation, and sports, and it also offers potential for use in robot teaching for reference motion generation.