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In this paper we introduce a novel Wearable Ultrasound Radial Muscle Activity Detection System (WURMADS) and a demonstration of its ability to recognize forearm muscle activities of amputee subjects to control a dexterous prosthetic hand. The system consists of control electronics to capture and record the ultrasound echo signals in real-time and two wearable bands embedded with eight ultrasound transducers. Based on the principles of Sonomyography, we recognized the intended isotonic finger gestures (trans-radial amputees) by analysing the echo patterns captured by eight single element transducers. Conventional non-invasive my electric detection strategy, Surface Electro Myography (sEMG), cannot reliably identify the deeper muscle activations in the forearm due to crosstalk and signal attenuation. It also suffers from signal degradation due to muscle fatigue and non-linearity. For this study we custom designed 1D single element waterproof transducers to be assembled in a radial structure. A real-time capturing electronic system was also designed, which is portable and wearable. The system operates at 5MHz, the frequency that demonstrated optimum performance for forearm applications. Ten trans-radial amputee subjects were employed in this study to capture data by executing five supervised gestures. The results obtained from offline analysis show that good gesture recognition rates can be achieved, while maintaining a decent correlation coefficient margin to distinguish gestures.
Hettiarachchi et al. (Thu,) studied this question.