Accuracy of the Microsoft Kinect sensor for measuring movement in people with Parkinson's disease
Accuracy of the Microsoft Kinect sensor for measuring movement in people with Parkinson's disease
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DOI：
10.1016/j.gaitpost.2014.01.008
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发表时间：
2014-04-01
期刊：
影响因子：
2.4
通讯作者：
Rochester, Lynn
中科院分区：
文献类型：
--
作者：
Galna, Brook;Barry, Gillian;Rochester, Lynn
背景资料：微软Kinect传感器（Kinect）可能是一种低成本的解决方案，用于帕金森病（PD）患者的临床和家庭运动症状评估。本研究的目的是建立的Kinect在测量临床相关运动的人与PD.Methods的准确性：9人PD和10个控制进行了一系列的运动，同时测量与Vicon三维运动分析系统（金标准）和Kinect。这些动作包括安静的站立，多向伸展和原地踏步和行走，以及统一帕金森病评定量表中的以下项目：手紧握，手指敲击，脚，腿敏捷性，椅子上升和手内旋。结果包括运动重复的平均时间和运动范围。结果：Kinect非常准确地测量了运动重复的时间（低偏差，95%的一致性限制<组平均值的10%，ICC> 0.9和Pearson r > 0.9）。然而，Kinect在测量空间特征方面的成功率各不相同，从坐到站等粗略运动的优秀（ICC = 0.989）到手紧握等精细运动的非常差（ICC = 0.012）。尽管如此，Kinect的结果与Vicon系统（Pearson's r > 0.8）获得的大多数movement.Conclusions：Kinect可以准确地测量临床相关运动的时间和总体空间特征，但对于较小的运动，如紧握手，则不具有相同的空间精度。(c)2014作者Elsevier B.V.出版，保留所有权利。
Background: The Microsoft Kinect sensor (Kinect) is potentially a low-cost solution for clinical and home-based assessment ofmovement symptoms in people with Parkinson's disease (PD). The purpose of this study was to establish the accuracy of the Kinect in measuring clinically relevant movements in people with PD.Methods: Nine people with PD and 10 controls performed a series of movements which were measured concurrently with a Vicon three-dimensional motion analysis system (gold-standard) and the Kinect. The movements included quiet standing, multidirectional reaching and stepping and walking on the spot, and the following items from the Unified Parkinson's Disease Rating Scale: hand clasping, finger tapping, foot, leg agility, chair rising and hand pronation. Outcomes included mean timing and range of motion across movement repetitions.Results: The Kinect measured timing of movement repetitions very accurately (low bias, 95% limits of agreement < 10% of the group mean, ICCs > 0.9 and Pearson's r > 0.9). However, the Kinect had varied success measuring spatial characteristics, ranging from excellent for gross movements such as sit- tostand (ICC =.989) to very poor for fine movement such as hand clasping (ICC =.012). Despite this, results from the Kinect related strongly to those obtained with the Vicon system (Pearson's r > 0.8) for most movements.Conclusions: The Kinect can accurately measure timing and gross spatial characteristics of clinically relevant movements but not with the same spatial accuracy for smaller movements, such as hand clasping. (c) 2014 The Authors. Published by Elsevier B.V. All rights reserved.