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Monitoring Motor Fluctuations in Parkinson's Disease Using a Waist-Worn Inertial Sensor

机译:使用腰部惯性传感器监测帕金森氏病中的电机波动

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Parkinson's disease (PD) is the second most common neurodegenera-tive disorder. First appreciable symptoms in PD are those related to an altered movement control. Current PD treatments temporally revert the symptoms, but they do not prevent disease's progression. At the beginning of the treatment, the antiparkinsonian effect of the medication is very evident and symptoms may completely disappear for hours; however, as disease progresses, motor fluctuations appear. Collecting precise information on the temporal course of fluctuations is essential for tailoring an optimal therapy in PD patients and is one of the main parameters in clinical trials. This paper presents an algorithm for wearable devices to automatically detect patient's motor fluctuations based on inertial sensors. The algorithm has been evaluated in 7 PD patients at their homes without supervision and performing their usual activities. Results are a mean sensitivity of 99.9% and a mean specificity of 99.9%.
机译:帕金森氏病(PD)是第二大最常见的神经退行性疾病。 PD中最明显的症状是与运动控制改变有关的症状。当前的PD治疗可以暂时缓解症状,但不能阻止疾病的进展。在治疗开始时,该药物的抗帕金森病作用非常明显,症状可能在数小时内完全消失。但是,随着疾病的发展,出现运动波动。收集有关波动时间过程的精确信息对于为PD患者量身定制最佳疗法至关重要,并且是临床试验中的主要参数之一。本文提出了一种可穿戴设备的算法,该算法可基于惯性传感器自动检测患者的运动波动。该算法已在7名PD患者的家中进行了评估,无需监督和执行其日常活动。结果是平均灵敏度为99.9%,平均特异性为99.9%。

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