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Intended gait speed prediction via swing limb kinematics applicable for patients with slow gait

机译:通过适用于步态缓慢的患者的Swing Limb运动学进行预定的步态速度预测

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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.
机译:准确预测预期的步态速度对于在机器人辅助步态培训期间促进激动肌活动至关重要。考虑到大多数患者发现难以以比较高的速度执行步态,因此预测模型也必须以缓慢的步态速度表现良好。此外,应该在机器人辅助之前给出用于信号处理的充足时间,使得患者不受不必要的阻力或滞后。在这里,作者提出通过当前摆动肢体的运动学来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,即使在慢速步态速度(<= 2km / h)中,作者的模型也表现良好,R-2值高达0.86。

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