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A Waist-Worn Inertial Measurement Unit for Long-Term Monitoring of Parkinson’s Disease Patients

机译:腰部惯性测量装置用于帕金森氏病患者的长期监测

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摘要

Inertial measurement units (IMUs) are devices used, among other fields, in health applications, since they are light, small and effective. More concretely, IMUs have been demonstrated to be useful in the monitoring of motor symptoms of Parkinson’s disease (PD). In this sense, most of previous works have attempted to assess PD symptoms in controlled environments or short tests. This paper presents the design of an IMU, called 9 × 3, that aims to assess PD symptoms, enabling the possibility to perform a map of patients’ symptoms at their homes during long periods. The device is able to acquire and store raw inertial data for artificial intelligence algorithmic training purposes. Furthermore, the presented IMU enables the real-time execution of the developed and embedded learning models. Results show the great flexibility of the 9 × 3, storing inertial information and algorithm outputs, sending messages to external devices and being able to detect freezing of gait and bradykinetic gait. Results obtained in 12 patients exhibit a sensitivity and specificity over 80%. Additionally, the system enables working 23 days (at waking hours) with a 1200 mAh battery and a sampling rate of 50 Hz, opening up the possibility to be used for other applications like wellbeing and sports.
机译:惯性测量单元(IMU)轻巧,小巧,有效,是健康领域中使用的其他设备。更具体地说,IMU已被证明可用于监测帕金森氏病(PD)的运动症状。从这个意义上讲,以前的大多数工作都试图在受控环境或简短测试中评估PD症状。本文介绍了一种称为9×3的IMU的设计,该IMU旨在评估PD症状,从而有可能在很长一段时间内在家中绘制患者症状图。该设备能够获取和存储原始惯性数据,以进行人工智能算法训练。此外,提出的IMU能够实时执行已开发和嵌入式学习模型。结果表明9×3具有很大的灵活性,可以存储惯性信息和算法输出,将消息发送到外部设备,并且能够检测到步态冻结和慢速运动步态。 12名患者获得的结果显示出80%以上的敏感性和特异性。此外,该系统可使用1200 mAh电池和50 Hz的采样率在23天(醒着的时间)工作,从而开辟了用于其他应用(例如健康和体育运动)的可能性。

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