Synchronous gesture recognition and muscle force estimation based on piezoelectric micromachined ultrasound transducer

Abstract

Early prosthetic control research mainly focused on motion intention recognition, but in recent years, study on control force has emerged. The simultaneous integration of motion intention recognition and control force estimation has significant practical value. This paper proposes an ultrasound control scheme using wearable device that enables synchronous intention recognition and accurate control force estimation. Eleven gestures abstracted from daily life are selected, with a force range of 0–100 % maximum voluntary contraction (MVC). The wearable device employed for muscle morphology monitoring consists of a piezoelectric micromachined ultrasound transducer (PMUT) and polymer encapsulation. It is small, lightweight, and eliminates the need for ultrasound gel, enhancing its practicality. Ultrasound echogenicity of two forearm muscles and corresponding output forces are simultaneously collected. We propose peak and location (PKL) feature and combine it with mean and standard deviation (MSD) feature to improve the accuracy of pattern recognition and force estimation. Experimental results show that during dynamic muscle contraction forces, the classification accuracy achieves 95.84 ± 1.48 %, while the synchronous estimation of forces yields a R2 correlation coefficient of 0.919 and a normalized root-mean-square deviation of 0.127. This scheme demonstrates the feasibility of PMUT-based ultrasound control for supporting synchronous gesture recognition and force estimation, and is expected to contribute to the practicality of prosthesis control.