Warsaw University of Technology, Faculty of Mechatronics, Institute of Metrology and Biomedical Engineering, A. Boboli 8 St., 02-525 Warsaw, Poland.
Sensors (Basel). 2021 Dec 15;21(24):8380. doi: 10.3390/s21248380.
Mechanomyography (MMG) is a technique of recording muscles activity that may be considered a suitable choice for human-machine interfaces (HMI). The design of sensors used for MMG and their spatial distribution are among the deciding factors behind their successful implementation to HMI. We present a new design of a MMG sensor, which consists of two coupled piezoelectric discs in a single housing. The sensor's functionality was verified in two experimental setups related to typical MMG applications: an estimation of the force/MMG relationship under static conditions and a neural network-based gesture classification. The results showed exponential relationships between acquired MMG and exerted force (for up to 60% of the maximal voluntary contraction) alongside good classification accuracy (94.3%) of eight hand motions based on MMG from a single-site acquisition at the forearm. The simplification of the MMG-based HMI interface in terms of spatial arrangement is rendered possible with the designed sensor.
肌电图描记术（MMG）是一种记录肌肉活动的技术，可被视为人机接口（HMI）的合适选择。用于 MMG 的传感器的设计及其空间分布是其成功应用于 HMI 的决定因素之一。我们提出了一种新的 MMG 传感器设计，它由两个耦合的压电盘组成，置于单个外壳中。该传感器的功能在与典型 MMG 应用相关的两个实验设置中得到了验证：在静态条件下估计力/MMG 关系，以及基于神经网络的手势分类。结果表明，在最大自主收缩的 60%以内，获得的 MMG 与施加的力之间存在指数关系，并且基于在前臂单点采集的 MMG，对手部八个动作的分类准确率高达 94.3%。所设计的传感器使得基于 MMG 的 HMI 接口在空间布置方面得以简化。
