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 mimick a human hand as illustrated in the link. 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创造仍是一个有待解决的问题。如何选择最佳的人机接口以实现自然控制仍然是一项挑战。表面肌电图作为最常用的方案，存在电极位移、汗液影响及肌肉疲劳等一系列难以克服的问题。基于超声成像的方法能够以更高的信噪比和更低的硬件需求（相比sEMG）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。基于所提出的框架，开发了可模拟人类手部运动的虚拟机械手仿真（参见链接）。所提出的四类手势分类模型准确率超过90%。