使用连续无监督活动评估基于腰部佩戴式三轴加速度计的跌倒检测算法。
Assessment of waist-worn tri-axial accelerometer based fall-detection algorithms using continuous unsupervised activities.
作者信息
Bourke Alan K, van de Ven Pepijn, Gamble Mary, O'Connor Raymond, Murphy Kieran, Bogan Elizabeth, McQuade Eamonn, Finucane Paul, Olaighin Gearoid, Nelson John
机构信息
Department of Electronic and Computer Engineering, Faculty of Science and Engineering, University of Limerick, Ireland.
出版信息
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:2782-5. doi: 10.1109/IEMBS.2010.5626364.
This study aims to evaluate a variety of existing and novel fall detection algorithms, for a waist mounted accelerometer based system. Algorithms were tested against a comprehensive data-set recorded from 10 young healthy subjects performing 240 falls and 120 activities of daily living and 10 elderly healthy subjects performing 240 scripted and 52.4 hours of continuous unscripted normal activities.
本研究旨在评估基于腰部佩戴式加速度计系统的各种现有和新型跌倒检测算法。针对从10名年轻健康受试者进行的240次跌倒和120次日常生活活动记录的综合数据集，以及10名老年健康受试者进行的240次预设活动和52.4小时连续无预设正常活动记录的综合数据集，对算法进行了测试。
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