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Use of a Single Wireless IMU for the Segmentation and Automatic Analysis of Activities Performed in the 3-m Timed Up Go Test

机译:使用单个无线IMU进行分段和自动分析在3-m计时上去测试中执行的活动

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摘要

Falls represent a major public health problem in the elderly population. The Timed Up & Go test (TU & Go) is the most used tool to measure this risk of falling, which offers a unique parameter in seconds that represents the dynamic balance. However, it is not determined in which activity the subject presents greater difficulties. For this, a feature-based segmentation method using a single wireless Inertial Measurement Unit (IMU) is proposed in order to analyze data of the inertial sensors to provide a complete report on risks of falls. Twenty-five young subjects and 12 older adults were measured to validate the method proposed with an IMU in the back and with video recording. The measurement system showed similar data compared to the conventional test video recorded, with a Pearson correlation coefficient of 0.9884 and a mean error of 0.17 ± 0.13 s for young subjects, as well as a correlation coefficient of 0.9878 and a mean error of 0.2 ± 0.22 s for older adults. Our methodology allows for identifying all the TU & Go sub–tasks with a single IMU automatically providing information about variables such as: duration of sub–tasks, standing and sitting accelerations, rotation velocity of turning, number of steps during walking and turns, and the inclination degrees of the trunk during standing and sitting.
机译:跌倒是老年人口中的主要公共卫生问题。 Timed Up&Go测试(TU&Go)是用来衡量这种跌倒风险的最常用工具,它以秒为单位提供了代表动态平衡的唯一参数。但是,尚不确定受试者在哪种活动中表现出更大的困难。为此,提出了一种使用单个无线惯性测量单元(IMU)的基于特征的分割方法,以便分析惯性传感器的数据以提供有关跌倒风险的完整报告。测量了25名年轻受试者和12名老年人,以验证在背部使用IMU并进行录像的建议方法。测量系统显示的数据与记录的常规测试视频相比相似,皮尔逊相关系数为0.9884,年轻受试者的平均误差为0.17±0.13 s,相关系数为0.9878,平均误差为0.2±0.22适用于老年人。我们的方法论允许通过单个IMU识别所有TU&Go子任务,该IMU自动提供有关变量的信息,例如:子任务的持续时间,站立和就座的加速度,转弯的旋转速度,行走和转弯时的步数以及站立和坐着时树干的倾斜度。

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