School of Mechanical Engineering, Hefei University of Technology, Hefei, 230009, China.
Chizhou Huayu Electronic Technology Company Ltd., Chizhou, 247100, China.
Med Biol Eng Comput. 2024 Sep;62(9):2825-2838. doi: 10.1007/s11517-024-03109-9. Epub 2024 May 3.
Surface electromyography (sEMG) signal is a kind of physiological signal reflecting muscle activity and muscle force. At present, the existing methods of recognizing human motion intention need more than two sensors to recognize more than two kinds of movements, the sensor pasting positions are special, and the hardware conditions for execution are high. In this work, a real-time motion intention recognition method based on Morse code is proposed and applied to the mechanical hand. The short-time and long-term muscle contraction signals collected by a single sEMG sensor were extracted and encoded with the Morse code method, and then the developed mapping method from Morse code to six hand movements were used to recognize hand movements. The average recognition accuracy of hand movements was 94.8704 ± 2.3556%, the average adjusting time was 34.89 s for all subjects, and the execution time of a single movement was 381 ms. The corresponding experiment video can be found in the attachment to show the experiment. The method proposed in this work is a method with one sensor to recognize six movements, low hardware conditions, high recognition accuracy, and insensitive to the difference of sensor pasting position.
表面肌电信号（sEMG）是一种反映肌肉活动和肌力的生理信号。目前，识别人体运动意图的现有方法需要两个以上的传感器来识别两种以上的运动，传感器粘贴位置特殊，执行的硬件条件较高。在这项工作中，提出了一种基于莫尔斯电码的实时运动意图识别方法，并将其应用于机械手。通过单个 sEMG 传感器采集的短期和长期肌肉收缩信号，采用莫尔斯电码方法进行提取和编码，然后采用开发的从莫尔斯电码到六种手部运动的映射方法来识别手部运动。手部运动的平均识别准确率为 94.8704±2.3556%，所有受试者的平均调整时间为 34.89s，单个运动的执行时间为 381ms。相应的实验视频可以在附件中找到，以展示实验。本工作提出的方法是一种用一个传感器识别六种运动的方法，具有硬件条件低、识别准确率高、对传感器粘贴位置差异不敏感的特点。
