Surface electromyography (sEMG) is a popular bio-signal used for controlling prostheses and finger gesture recognition mechanisms. Myoelectric prostheses are costly, and most commercially available sEMG acquisition systems are not suitable for real-time gesture recognition. In this paper, a method of acquiring sEMG signals using novel low-cost, active, dry-contact, flexible sensors has been proposed. Since the active sEMG sensor was developed to be used along with a bionic arm, the sensor was tested for its ability to acquire sEMG signals that could be used for real-time classification of five selected gestures. In a study of 4 subjects, the average classification accuracy for real-time gesture classification using the active sEMG sensor system was 85%. The common-mode rejection ratio of the sensor was measured to 59 dB, and thus the sensor's performance was not substantially limited by its active circuitry. The proposed sensors can be interfaced with a variety of amplifiers to perform fully wearable sEMG acquisition. This satisfies the need for a low-cost sEMG acquisition system for prostheses.

中文翻译：

---

用于仿生手臂的低成本主动干接触表面肌电传感器

表面肌电图 (sEMG) 是一种流行的生物信号，用于控制假肢和手指手势识别机制。肌电假体价格昂贵，大多数市售的 sEMG 采集系统不适合实时手势识别。在本文中，提出了一种使用新型低成本、有源、干接触、柔性传感器获取 sEMG 信号的方法。由于主动 sEMG 传感器被开发为与仿生手臂一起使用，因此测试了该传感器获取 sEMG 信号的能力，该信号可用于五个选定手势的实时分类。在对 4 名受试者的研究中，使用主动 sEMG 传感器系统进行实时手势分类的平均分类准确率为 85%。传感器的共模抑制比测量为 59 dB，因此传感器的 其性能基本上不受其有源电路的限制。所提出的传感器可以与各种放大器连接，以执行完全可穿戴的 sEMG 采集。这满足了对用于假肢的低成本 sEMG 采集系统的需求。