Walsh Lorcan, Doyle Julie, Smith Erin, Inomata Akihiro, Bond Rodd
Annu Int Conf IEEE Eng Med Biol Soc. 2015 Aug;2015:3719-22. doi: 10.1109/EMBC.2015.7319201.
This paper describes the collection of real-world gait data in a cohort of 7 community living older adults, who have fallen at least once in the previous year, while they live in a smart apartment for four days. It describes the approach used to collect various gait metrics, from inertial sensors placed on the lower shanks, where gait bouts can be contextualised by smart home data. Results from this study are presented with a brief discussion into the smart-home based contextualisation of outliers in the gait data. Future work will investigate the normative ranges of various gait metrics, and how such real-world gait data may be integrated into clinical practice.
本文描述了在一个由7名社区居住的老年人组成的队列中收集真实世界步态数据的情况。这些老年人在前一年至少跌倒过一次，他们在一个智能公寓中居住了四天。文中介绍了用于收集各种步态指标的方法，这些指标来自放置在小腿下部的惯性传感器，通过智能家居数据可以将步态发作情况进行背景化分析。本文呈现了该研究的结果，并对基于智能家居的步态数据异常值背景化进行了简要讨论。未来的工作将研究各种步态指标的正常范围，以及如何将这些真实世界的步态数据整合到临床实践中。
