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A metric for upper extremity functional range of motion analysis in long-term stroke recovery using wearable motion sensors and posture cubics

机译:使用可穿戴运动传感器和姿势立方体的长期卒中恢复中的上肢运动分析功能范围的度量

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We investigate an approach to analyse and represent the functional range of motion (fROM) in patients after stroke during long-term rehabilitation in a day-care centre. Movement data of patients after stroke were recorded during free activities of living (ADL) and one-to-one (OTO) therapies using wearable inertial motion sensors. Using a gradient descent sensor fusion algorithm, we estimated orientation of upper body extremities and described extremity positions as frequency statistics in spatial posture cubics. We visualised the fROM and compared sensor-based posture representation with video reference during OTO. To illustrate our approach, we analysed differences in affected and non-affected arm use in three typical patients after stroke across multiple weeks. Our analysis revealed differences in body sides as well as between ADL and OTO. Posture cubics may provide clinicians with an intuitive tool for longitudinal fROM analysis.
机译:我们研究了一种在日间护理中心进行长期康复期间中风后患者的运动功能范围(fROM)的分析和表示方法。使用可穿戴的惯性运动传感器在自由活动(ADL)和一对一(OTO)治疗期间记​​录中风后患者的运动数据。使用梯度下降传感器融合算法,我们估计了上肢四肢的方位,并将四肢的位置描述为空间姿势立方体中的频率统计信息。我们对fROM进行了可视化,并在OTO期间将基于传感器的姿势表示与视频参考进行了比较。为了说明我们的方法,我们分析了三名典型卒中患者在数周内受影响和未受影响的手臂使用的差异。我们的分析揭示了身体两侧以及ADL和OTO之间的差异。姿势立方可以为临床医生提供用于纵向fROM分析的直观工具。

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