The creation of unique control methods for a hand prosthesis is still a problem that has to be addressed. The best choice of a human-machine interface (HMI) that should be used to enable natural control is still a challenge. Surface electromyography (sEMG), the most popular option, has a variety of difficult-to-fix issues (electrode displacement, sweat, fatigue). The ultrasound imaging-based methodology offers a means of recognising complex muscle activity and configuration with a greater SNR and less hardware requirements as compared to sEMG. In this study, a prototype system for high frame rate ultrasound imaging for prosthetic arm control is proposed. Using the proposed framework, a virtual robotic hand simulation is developed that can mimic a human hand as illustrated in the link [10]. The proposed classification model simulating four hand gestures has a classification accuracy of more than 90%.

翻译：手部假肢的独特控制方法构建仍是一个亟待解决的问题。如何选择最佳的人机接口以实现自然控制仍是一项挑战。表面肌电图作为最常用的方案，存在诸多难以克服的问题（电极移位、汗液干扰、肌肉疲劳）。相比表面肌电图，基于超声成像的方法能以更高的信噪比和更少的硬件需求识别复杂的肌肉活动与构型。本研究提出了一种用于假肢手臂控制的高帧率超声成像原型系统。利用该框架，开发了可模拟人手的虚拟机械手仿真系统（详见文献[10]）。所提出的分类模型可识别四种手势，分类准确率超过90%。