Accurate prediction of intended gait speed is crucial for facilitating volitional muscle activity during robot-assisted gait training. Considering that most patients find it difficult to perform gait at relatively high speeds, it is also imperative that the prediction model performs well at slow gait speed. Furthermore, ample time for signal processing should be given prior to robot assistance such that the patient is not subjected to unwanted resistance or lag. Here, the authors propose to predict the intended speed of the contralateral limb via kinematics of the current swing limb. Three lower-limb positions were evaluated using an inertial measurement unit sensor during treadmill gait sessions. The results suggest that the authors’ model performs well even during slow gait speeds ( ≤ 2 km / h ) with R 2 values as high as 0.86.

中文翻译：

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通过摆动肢体运动学进行预期步态速度预测适用于步态缓慢患者

准确预测预期步态速度对于在机器人辅助步态训练期间促进意志性肌肉活动至关重要。考虑到大多数患者难以在相对较高的速度下进行步态，因此预测模型在慢速步态下也表现良好也势在必行。此外，应在机器人协助之前给予足够的信号处理时间，以免患者受到不必要的阻力或滞后。在这里，作者建议通过当前摆动肢体的运动学预测对侧肢体的预期速度。在跑步机步态会话期间使用惯性测量单元传感器评估三个下肢位置。结果表明，即使在 R 2 值高达 0.86 的低步态速度 (≤ 2 km / h ) 下，作者的模型也能表现良好。