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运动多样性和复杂性随着中风后手臂功能障碍的减少而增加:运动体验质量可能是可穿戴反馈的目标。

Movement Diversity and Complexity Increase as Arm Impairment Decreases After Stroke: Quality of Movement Experience as a Possible Target for Wearable Feedback.

出版信息

IEEE Trans Neural Syst Rehabil Eng. 2024;32:2961-2970. doi: 10.1109/TNSRE.2024.3439669. Epub 2024 Aug 20.

Abstract

Upper extremity (UE) impairment is common after stroke resulting in reduced arm use in daily life. A few studies have examined the use of wearable feedback of the quantity of arm movement to promote recovery, but with limited success. We posit that it may be more effective to encourage an increase in beneficial patterns of movement practice - i.e. the overall quality of the movement experience - rather than simply the overall amount of movement. As a first step toward testing this idea, here we sought to identify statistical features of the distributions of daily arm movements that become more prominent as arm impairment decreases, based on data obtained from a wrist IMU worn by 22 chronic stroke participants during their day. We identified several measures that increased as UE Fugl-Meyer (UEFM) score increased: the fraction of movements achieved at a higher speed, forearm postural diversity (quantified by kurtosis of the tilt-angle), and forearm postural complexity (quantified by sample entropy of tilt angle). Dividing participants into severe, moderate, and mild impairment groups, we found that forearm postural diversity and complexity were best able to distinguish the groups (Cohen's D =1.1, and 0.99, respectively) and were also the best subset of predictors for UEFM score. Based on these findings coupled with theories of motor learning that emphasize the importance of variety and challenge in practice, we suggest that using these measures of diversity and complexity in wearable rehabilitation could provide a basis to test whether the quality of the daily movement experience is therapeutic.

摘要

上肢(UE)损伤在中风后很常见,导致日常生活中手臂使用减少。一些研究已经检查了使用可穿戴的手臂运动数量反馈来促进恢复,但效果有限。我们假设,鼓励有益的运动模式练习——即运动体验的整体质量——而不仅仅是运动的总体数量,可能会更有效。作为测试这一想法的第一步,我们根据 22 名慢性中风参与者在日常生活中佩戴手腕 IMU 获得的数据,试图确定手臂运动分布的统计特征,这些特征随着手臂损伤的减少而变得更加明显。我们确定了几个随着 UE Fugl-Meyer(UEFM)评分增加而增加的指标:以更高速度实现的运动比例、前臂姿势多样性(由倾斜角度的峰度量化)和前臂姿势复杂性(由倾斜角度的样本熵量化)。将参与者分为严重、中度和轻度损伤组,我们发现前臂姿势多样性和复杂性最能区分组(Cohen's D 分别为 1.1 和 0.99),也是 UEFM 评分的最佳预测因子子集。基于这些发现以及强调实践中多样性和挑战性重要性的运动学习理论,我们建议在可穿戴康复中使用这些多样性和复杂性指标,可以提供一个基础来测试日常运动体验的质量是否具有治疗作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70f2/11500827/00b85ba931bf/nihms-2017996-f0001.jpg

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