Objective. Body-Machine Interfaces (BoMIs) establish a way to operate a variety of devices, allowing their users to extend the limits of their motor abilities by exploiting the redundancy of muscles and motions that remain available after spinal cord injury or stroke. Here, we considered the integration of two types of signals, motion signals derived from inertial measurement units (IMUs) and muscle activities recorded with electromyography (EMG), both contributing to the operation of the BoMI. Approach. A direct combination of IMU and EMG signals might result in inefficient control due to the differences in their nature. Accordingly, we used a nonlinear-regression-based approach to predict IMU from EMG signals, after which the predicted and actual IMU signals were combined into a hybrid control signal. The goal of this approach was to provide users with the possibility to switch seamlessly between movement and EMG control, using the BoMI as a tool for promoting t...

中文翻译：

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混合的机体界面，整合了来自肌肉和运动的信号。

目的。人机界面（BoMI）建立了一种操作各种设备的方式，使用户可以利用脊髓损伤或中风后仍然可以利用的肌肉和动作的冗余来扩展其运动能力的极限。在这里，我们考虑了两种信号的集成，即从惯性测量单位（IMU）导出的运动信号和用肌电图（EMG）记录的肌肉活动，这两者均有助于BoMI的运行。方法。IMU和EMG信号的直接组合可能由于其性质的差异而导致控制效率低下。因此，我们使用基于非线性回归的方法从EMG信号中预测IMU，然后将预测的IMU和实际的IMU信号组合为混合控制信号。