IEEE Trans Biomed Eng. 2022 Jan;69(1):63-74. doi: 10.1109/TBME.2021.3087137. Epub 2021 Dec 23.
Surface EMG-driven modelling has been proposed as a means to control assistive devices by estimating joint torques. Implanted EMG sensors have several advantages over wearable sensors but provide a more localized information on muscle activity, which may impact torque estimates. Here, we tested and compared the use of surface and intramuscular EMG measurements for the estimation of required assistive joint torques using EMG driven modelling.
Four healthy subjects and three incomplete spinal cord injury (SCI) patients performed walking trials at varying speeds. Motion capture marker trajectories, surface and intramuscular EMG, and ground reaction forces were measured concurrently. Subject-specific musculoskeletal models were developed for all subjects, and inverse dynamics analysis was performed for all individual trials. EMG-driven modelling based joint torque estimates were obtained from surface and intramuscular EMG.
The correlation between the experimental and predicted joint torques was similar when using intramuscular or surface EMG as input to the EMG-driven modelling estimator in both healthy individuals and patients.
We have provided the first comparison of non-invasive and implanted EMG sensors as input signals for torque estimates in healthy individuals and SCI patients.
Implanted EMG sensors have the potential to be used as a reliable input for assistive exoskeleton joint torque actuation.
表面肌电驱动建模已被提议通过估计关节扭矩来控制辅助设备。植入式肌电传感器相对于可穿戴传感器具有多项优势，但可提供关于肌肉活动的更局部信息，这可能会影响扭矩估计。在这里，我们测试并比较了使用表面肌电和肌内肌电测量来估计使用肌电驱动建模所需的辅助关节扭矩。
四名健康受试者和三名不完全性脊髓损伤（SCI）患者以不同速度进行行走试验。同时测量运动捕捉标记轨迹、表面肌电和肌内肌电以及地面反作用力。为所有受试者开发了特定于个体的肌肉骨骼模型，并对所有个体试验进行了逆动力学分析。从表面肌电和肌内肌电获得基于肌电驱动建模的关节扭矩估计。
在健康个体和 SCI 患者中，将肌内或表面肌电用作 EMG 驱动建模估计器的输入时，实验和预测的关节扭矩之间的相关性相似。
我们首次比较了非侵入性和植入式肌电传感器作为健康个体和 SCI 患者扭矩估计的输入信号。
植入式肌电传感器有可能成为辅助外骨骼关节扭矩致动的可靠输入。
