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On-Body Sensor Position Identification with a Simple, Robust and Accurate Method, Validated in Patients with Parkinson’s Disease*

机译:通过简单,稳健且准确的方法对人体传感器位置进行识别,已在帕金森氏病患者中得到验证*

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The aim of this work is to implement and validate an automated method for the localization of body-worn inertial sensors. Often, body-sensor networks with inertial measurement units (IMU) used in rehabilitation and ambient monitoring of patients with movement disorders, require specific markings or labels for the correct body placement. This introduces a burden, which, especially for ambient monitoring, could lead to errors or reduced adherence. We propose a method to automatically identify sensors attached on a predefined set of body placements, namely, wrists, shanks and torso. The method was used in a multi-site clinical trial with Parkinson’s disease patients and in 45 sessions it identified sensor placement on torso, wrists and shanks with 100% accuracy, discriminated between left and right shank with 100% accuracy and between left and right wrist with 98% accuracy. This is remarkable, considering the presence of parkinsonian motor symptoms causing abnormal movement patterns, such as dyskinesia.Clinical Relevance- This method can facilitate home monitoring of patients with movement disorders
机译:这项工作的目的是实现和验证一种自动方法,用于对人体佩戴的惯性传感器进行定位。带有惯性测量单元(IMU)的身体传感器网络通常用于运动障碍患者的康复和环境监测,需要正确的身体位置标记或标签。这带来了负担,特别是对于环境监测而言,可能导致错误或减少依从性。我们提出了一种方法,用于自动识别附着在一组预定的身体位置(即手腕,小腿和躯干)上的传感器。该方法已在帕金森氏病患者的多站点临床试验中使用,并在45个疗程中以100%的准确度识别了传感器在躯干,腕部和小腿上的位置,以100%的准确度区分了左,右小腿以及左右手腕之间的传感器准确度达98%。考虑到存在帕金森氏运动症状引起异常运动模式(例如运动障碍)的情况,这一点非常显着。临床意义-这种方法可以帮助对运动障碍患者进行家庭监护

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