Capturing habitual, in-home gait parameter trends using an inexpensive depth camera.
Capturing habitual, in-home gait parameter trends using an inexpensive depth camera.
复制标题
使用廉价的深度相机捕捉习惯性的家庭步态参数趋势。
DOI：
10.1109/embc.2012.6347142
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
Skubic,Marjorie
中科院分区：
文献类型：
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作者：
Stone,ErikE;Skubic,Marjorie
本研究报告了四个月内连续测量五名老年人在家中的步行速度、步幅时间和步幅长度等步态参数的结果。使用廉价的环境安装深度相机 Microsoft Kinect 被动测量步态参数。研究表明，出于多种目的测量人的步态非常重要，从跌倒风险评估到早期发现认知障碍等健康问题。然而，此类评估通常很少进行，并且大多数当前技术不适合连续、长期使用。在这项工作中，在四间公寓（总共有五名居民）中部署了一个 Microsoft Kinect 传感器。提出了一种根据在家中确定的步行序列的数据生成步行速度、步幅时间和步幅长度趋势的方法，以及对这项工作进行监测的五名参与者的趋势估计。
Results are presented for measuring the gait parameters of walking speed, stride time, and stride length of five older adults continuously, in their homes, over a four month period. The gait parameters were measured passively, using an inexpensive, environmentally mounted depth camera, the Microsoft Kinect. Research has indicated the importance of measuring a person's gait for a variety of purposes from fall risk assessment to early detection of health problems such as cognitive impairment. However, such assessments are often done infrequently and most current technologies are not suitable for continuous, long term use. For this work, a single Microsoft Kinect sensor was deployed in four apartments, containing a total of five residents. A methodology for generating trends in walking speed, stride time, and stride length based on data from identified walking sequences in the home is presented, along with trend estimates for the five participants who were monitored for this work.