一个可穿戴系统在现实世界的运动中实验性膝关节疼痛:习惯化和运动适应

IF 4.8 2区 医学 Q2 ENGINEERING, BIOMEDICAL
Jesse M. Charlton;Liam H. Foulger;Calvin Kuo;Jean-Sébastien Blouin
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引用次数: 0

摘要

我们开发了一种新颖的可穿戴系统,将运动传感和电刺激实时结合起来,研究新环境下的运动适应。在两个实验中,我们建立了系统开发所需的关键信息,包括:1)疼痛习惯模式和行走时膝关节疼痛的运动适应;2)电刺激强度与痛觉的函数模型;3)疼痛强度的步态相位依赖性调节。在三次10分钟的步行训练中,我们观察到明显的疼痛习惯化(p1/10),尽管需要分段线性模型(Adj R $^{{2}} =0.874$)或指数模型(Adj R $^{{2}} =0.869$)来拟合刺激强度范围(0-5/10)的感知数据。最后,参与者没有报告在强直性电刺激下行走时疼痛强度的步态相位依赖性调节。我们的可穿戴系统在以前不可能的新环境中支持新的运动适应实验。这些结果表明,该系统在复杂运动(步行)中诱导局部疼痛感知和运动适应,同时为未来的疼痛实验研究提供指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Wearable System for Experimental Knee Pain During Real-World Locomotion: Habituation and Motor Adaptation
We developed a novel, wearable system that couples motion sensing and electrical stimulation in real-time to study motor adaptation in new environments. In two experiments we established key information needed in the development of our system including 1) pain habituation patterns and motor adaptations to knee pain while walking; 2) a model of electrical stimulation magnitude as a function of pain perception; and 3) gait-phase-dependent modulation of pain intensity. Over three 10-minute walking bouts, we observed significant pain habituation (p<0.001)>1/10, though a piecewise linear (Adj R $^{{2}} =0.874$ ) or exponential model (Adj R $^{{2}} =0.869$ ) was required to fit the perception data across the stimulus intensity range (0-5/10). Finally, participants did not report gait-phase-dependent modulation of pain intensity while walking with tonic electrical stimulation. Our wearable system supports new motor adaptation experiments in novel contexts not previously possible. These results show the system induces localized pain perceptions and motor adaptations in complex movements (walking) while providing guidelines to structure future experimental pain studies.
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来源期刊
CiteScore
8.60
自引率
8.20%
发文量
479
审稿时长
6-12 weeks
期刊介绍: Rehabilitative and neural aspects of biomedical engineering, including functional electrical stimulation, acoustic dynamics, human performance measurement and analysis, nerve stimulation, electromyography, motor control and stimulation; and hardware and software applications for rehabilitation engineering and assistive devices.
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