An inertial sensor based balance and gait analysis system
An inertial sensor based balance and gait analysis system
复制标题
基于惯性传感器的平衡和步态分析系统
DOI：
10.1109/iscas.2015.7169227
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
M. Pai
中科院分区：
文献类型：
--
作者：
Wei;P. Chung;Guo Liang Yang;Chien;Yu;M. Pai
起跑计时试验(Time-Up and Go Test，TUGT)是临床上常见的老年人运动试验。目前多采用人工测量，耗费人力资源，测量精度不高，对复杂参数的测量能力有限。在本文中，我们提出了一个由三个基于惯性传感器的测量部件、一个遥控器和一个用于TUGT自动平衡和步态分析的分析软件组成的系统。该系统使用方便，软件可自动测量站立时间、坐姿时间和测试总时间的时间间隔。此外，该系统还可以获取步态信息，包括步态时间、摆动时间和站立时间。为了验证该系统，我们将其性能与以视频为黄金标准的秒表的性能进行了比较。结果表明，该系统不仅提供了一种方便的测量方式，而且获得了比秒表更准确、更可靠的测量结果。我们使用这个系统来比较阿尔茨海默病患者(ADS)和健康控制者(HCS)。结果表明，与HCS相比，ADS在服用TUGT时需要更长的站立时间、坐着时间和总时间。步态时间、摆动时间和站立时间也都长于普通步态。这种友好的系统在跟踪诊断的长期模式方面提供了很高的潜力。
Time-up and Go Test (TUGT) is a common clinical motility test for the elderly. Currently it is measured manually, which is human resource consuming, less accurate, and limited in capability of measuring sophisticated parameters. In this paper, we propose a system consisting of three inertial-sensor-based measuring components, a remote controller, and an analysis software for automatic balance and gait analysis in TUGT. This system is designed to be of easy use with the software automatically measuring the time intervals of stand-up time, sit-down time, and the total time of test. In addition, the system can also obtain the gait information of stride time, swing time, and stance time. To validate the system, we compared the performance with that obtained from stopwatch using videos as the gold standard. The results indicate that the system not only provides a convenient way of measurement but also achieves higher accurate and reliable measurement results than using stopwatch. We use this system to compare the Alzheimer's disease patients (ADs) with health controllers (HCs). The results show that the ADs need longer stand-up time, sit-down time, and total time while taking the TUGT compared to the HCs. The stride time, swing time, and stance time are also longer than the HCs'. Such a friendly system provides high potential in tracking long-time patterns for diagnosis.
影响因子：
3.2
作者：
Shumway-Cook, A;Brauer, S;Woollacott, M
通讯作者：
Woollacott, M