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Wearable Assistant for Parkinson’s Disease Patients With the Freezing of Gait Symptom

机译:帕金森氏病患者步态冻结的可穿戴助手

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摘要

In this paper, we present a wearable assistant for Parkinson's disease (PD) patients with the freezing of gait (FOG) symptom. This wearable system uses on-body acceleration sensors to measure the patients' movements. It automatically detects FOG by analyzing frequency components inherent in these movements. When FOG is detected, the assistant provides a rhythmic auditory signal that stimulates the patient to resume walking. Ten PD patients tested the system while performing several walking tasks in the laboratory. More than 8 h of data were recorded. Eight patients experienced FOG during the study, and 237 FOG events were identified by professional physiotherapists in a post hoc video analysis. Our wearable assistant was able to provide online assistive feedback for PD patients when they experienced FOG. The system detected FOG events online with a sensitivity of 73.1% and a specificity of 81.6%. The majority of patients indicated that the context-aware automatic cueing was beneficial to them. Finally, we characterize the system performance with respect to the walking style, the sensor placement, and the dominant algorithm parameters.
机译:在本文中,我们为帕金森病(PD)伴有步态冻结(FOG)症状的患者提供了一种可穿戴助手。该可穿戴系统使用人体加速度传感器来测量患者的运动。它通过分析这些运动中固有的频率成分来自动检测FOG。当检测到FOG时,助手会提供有节奏的听觉信号,以刺激患者恢复行走。十名PD患者在实验室中执行几个步行任务时对其进行了测试。记录了超过8小时的数据。在研究期间,有8位患者经历了FOG,并且由专业理疗师在事后视频分析中确定了237例FOG事件。当PD患者经历FOG时,我们的可穿戴助手能够为其提供在线辅助反馈。该系统在线检测FOG事件,灵敏度为73.1%,特异性为81.6%。大多数患者表示情境感知自动提示对他们有益。最后,我们根据行走方式,传感器位置和主要算法参数来表征系统性能。

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