Medical Robotics and Biosignal Processing Laboratory, Unidad Profesional Interdisciplinaria de Biotecnología, Instituto Politécnico Nacional, Mexico City 07340, Mexico.
Facultad de Ingeniería, Universidad de Antioquia, Medellin 050010, Colombia.
Sensors (Basel). 2022 Aug 9;22(16):5931. doi: 10.3390/s22165931.
Surface electromyography (sEMG) is a non-invasive measure of electrical activity generated due to muscle contraction. In recent years, sEMG signals have been increasingly used in diverse applications such as rehabilitation, pattern recognition, and control of orthotic and prosthetic systems. This study presents the development of a versatile multi-channel sEMG low-cost wearable band system to acquire 4 signals. In this case, the signals acquired with the proposed device have been used to detect hand movements. However, the WyoFlex band could be used in some sections of the arm or the leg if the section's diameter matches the diameter of the WyoFlex band. The designed WyoFlex band was fabricated using three-dimensional (3D) printing techniques employing thermoplastic polyurethane and polylactic acid as manufacturing materials. Then, the proposed wearable electromyographic system (WES) consists of 2 WyoFlex bands, which simultaneously allow the wireless acquisition of 4 sEMG channels of each forearm. The collected sEMG can be visualized and stored for future post-processing stages using a graphical user interface designed in Node-RED. Several experimental tests were conducted to verify the performance of the WES. A dataset with sEMG collected from 15 healthy humans has been obtained as part of the presented results. In addition, a classification algorithm based on artificial neural networks has been implemented to validate the usability of the collected sEMG signals.
表面肌电图（sEMG）是一种非侵入性的测量方法，用于测量由于肌肉收缩而产生的电活动。近年来，sEMG 信号在康复、模式识别和矫形器和假肢系统的控制等各种应用中得到了越来越多的应用。本研究提出了一种通用的多通道 sEMG 低成本可穿戴带系统的开发，以获取 4 个信号。在这种情况下，所提出的设备获取的信号被用于检测手部运动。然而，如果该部分的直径与 WyoFlex 带的直径匹配，WyoFlex 带可以在手臂或腿部的某些部分使用。设计的 WyoFlex 带使用三维（3D）打印技术制造，采用热塑性聚氨酯和聚乳酸作为制造材料。然后，所提出的可穿戴肌电图系统（WES）由两个 WyoFlex 带组成，这两个带同时允许每个前臂无线采集 4 个 sEMG 通道。使用在 Node-RED 中设计的图形用户界面可以可视化和存储采集到的 sEMG，以便进行未来的后处理阶段。进行了多项实验测试来验证 WES 的性能。作为提出的结果的一部分，已经获得了一个从 15 个健康人采集的 sEMG 数据集。此外，还实现了基于人工神经网络的分类算法来验证所采集的 sEMG 信号的可用性。
