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用可穿戴传感器进行散步分析,用于孤立的REM睡眠行为障碍与转换相关:一项探索性研究
Shanshan Cen1, Hui Zhang1,2, Yuan Li1,2
1Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China.
Journal of Parkinson's disease
|June 7, 2024
概括
在孤立的快速眼动睡眠行为障碍 (iRBD) 患者中,细微的步态变化可以预测转化为α-synucleinopathies的现象转化. 使用可穿戴传感器的步行分析确定了步伐长度不对称性作为疾病进展的关键预测因素.
科学领域:
- 神经学 神经学
- 生物医学工程 生物医学工程
- 睡眠医学 睡眠医学
背景情况:
- 步态障碍是像帕金森病这样的α-synucleinopathies的关键运动症状.
- 在疾病表现之前,在孤立的快速眼动睡眠行为障碍 (iRBD) 患者中观察到微妙的步态变化.
- 目前尚不清楚步态分析是否可以预测iRBD患者的转化.
研究的目的:
- 在iRBD患者中调查微妙的步态变化.
- 确定使用可穿戴传感器的步态分析是否可以预测iRBD转化为α-synucleinopathies的现象转化.
主要方法:
- 研究人员招募了31名iRBD患者和33名健康对照 (HC).
- 参与者在正常,快速和双重任务行走时,在手腕,脚和干上戴着6个惯性传感器.
- 在基线和随访期间分析了步行参数.
主要成果:
- 减少手臂运动和增加步态变化 (步幅长度,时间,速度) 在基线上区分了转换器与HC.
- 在平均5.40年的随访后,10名iRBD患者转化为神经退行性疾病.
- 在正常行走期间更高的步伐长度不对称性预测了更早地转化为α-synucleinopathies (aHR 4.468,p=0.038).
结论:
- 在iRBD患者中,脚步长度不对称与向α-synucleinopathies的进展有关.
- 基于可穿戴传感器的步态分析显示了iRBD中查,监测和风险分层的潜力.
- 这种方法可以帮助识别疾病修饰疗法试验的候选者.
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