Validity of using tri-axial accelerometers to measure human movement - Part I: Posture and movement detection.
Validity of using tri-axial accelerometers to measure human movement - Part I: Posture and movement detection.
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DOI：
10.1016/j.medengphy.2013.06.005
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发表时间：
2014-02
影响因子：
2.2
通讯作者：
Kaufman K
中科院分区：
文献类型：
--
作者：
Lugade V;Fortune E;Morrow M;Kaufman K
需要一种用于识别自由生活环境中的运动的鲁棒方法来客观地测量身体活动。本研究的目的是验证识别姿势的方向和运动的加速度数据对视觉检查从视频记录。使用放置在腰部和大腿上的三轴加速度计，确定了站立、坐下和躺下的静态方向，以及步行、慢跑和姿势之间的转换的动态运动。此外，受试者以自选的慢速、舒适和快速行走和慢跑。识别的任务进行组合的信号幅度面积，连续小波变换和加速度计的方向。在实验室中对12名健康成年人进行了研究，两名研究人员在每秒的视频观察中确定任务。除过渡外，所有活动的评分员间信度的组内相关系数均大于0.95。结果显示出较高的有效性，坐着和躺着的灵敏度和阳性预测值大于85%，步行和慢跑的灵敏度和阳性预测值大于90%。算法和视频之间识别准确性的最大分歧发生在受试者被要求在站立或坐下时坐立不安时。在变速任务中，步态被正确识别为0.1 m/s和4.8 m/s之间的速度。这项研究包括一系列步行速度和自然运动，例如静态姿势时的坐立不安，表明加速度计数据可用于识别普通人群的方向和运动。
A robust method for identifying movement in the free-living environment is needed to objectively measure physical activity. The purpose of this study was to validate the identification of postural orientation and movement from acceleration data against visual inspection from video recordings. Using tri-axial accelerometers placed on the waist and thigh, static orientations of standing, sitting, and lying down, as well as dynamic movements of walking, jogging and transitions between postures were identified. Additionally, subjects walked and jogged at self-selected slow, comfortable, and fast speeds. Identification of tasks was performed using a combination of the signal magnitude area, continuous wavelet transforms and accelerometer orientations. Twelve healthy adults were studied in the laboratory, with two investigators identifying tasks during each second of video observation. The intraclass correlation coefficients for inter-rater reliability were greater than 0.95 for all activities except for transitions. Results demonstrated high validity, with sensitivity and positive predictive values of greater than 85% for sitting and lying, with walking and jogging identified at greater than 90%. The greatest disagreement in identification accuracy between the algorithm and video occurred when subjects were asked to fidget while standing or sitting. During variable speed tasks, gait was correctly identified for speeds between 0.1m/s and 4.8m/s. This study included a range of walking speeds and natural movements such as fidgeting during static postures, demonstrating that accelerometer data can be used to identify orientation and movement among the general population.
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发表时间：
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影响因子：
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