Stone Erik E, Anderson Derek, Skubic Marjorie, Keller James M
Electrical and Computer Engineering Department at the University of Missouri, Columbia, MO 65211, USA.
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:1119-22. doi: 10.1109/IEMBS.2010.5627102.
In this paper, we present a method for extracting footfall locations from three dimensional voxel data created from a pair of silhouettes. With the growth of the elderly population, there is a need for passive monitoring of physical activity to allow older adults to continue living in independent settings. Prior research using anonymized video data has shown good results in passively acquiring information useful for assessing physical function; and, additionally, research has shown that video data anonymized through the use of silhouettes alleviates privacy concerns of older adults towards the technology. Previous work in acquiring gait information from voxel data has not included a technique for identifying individual footfall locations, from which additional information useful for assessing asymmetric gait patterns and other physical parameters may be obtained. Furthermore, visualization of the footfall locations during a walking sequence may provide additional insight to care providers for assessing physical function. To evaluate our approach, participants were asked to walk across a GAITRite electronic mat, used to validate our results, while also being monitored by our camera system. Results show good agreement between the footfalls extracted by our system and those from the GAITRite.
在本文中，我们提出了一种从由一对轮廓创建的三维体素数据中提取脚步落点位置的方法。随着老年人口的增长，需要对身体活动进行被动监测，以使老年人能够继续在独立环境中生活。先前使用匿名视频数据的研究在被动获取有助于评估身体功能的信息方面取得了良好成果；此外，研究表明，通过使用轮廓进行匿名处理的视频数据减轻了老年人对该技术的隐私担忧。先前从体素数据中获取步态信息的工作尚未包括识别单个脚步落点位置的技术，而从这些位置可以获得有助于评估不对称步态模式和其他身体参数的额外信息。此外，步行序列中脚步落点位置的可视化可为护理人员评估身体功能提供更多见解。为了评估我们的方法，我们要求参与者走过一块GAITRite电子垫（用于验证我们的结果），同时我们的摄像系统也对其进行监测。结果表明，我们的系统提取的脚步落点与GAITRite的结果之间具有良好的一致性。
