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基于多传感器数据融合的跌倒检测算法

A fall detection algorithm based on multi-sensor data

作者: 李坤  姜萍萍  颜国正 
单位:上海交通大学电子信息与电气工程学院医学精密工程与智能仪器研究所(上海200240)
关键词: 惯性传感器;多传感器数据融合;加速度;跌倒检测算法 
分类号:R318.04
出版年·卷·期(页码):2016·35·5(483-488)
摘要:

目的 跌倒在老年人生活中是一种常见的现象,是致使老年人发病和死亡的主要原因之一。实时的跌倒检测系统能够及时报警,缩短等待救治的时间,减少由跌倒引起的意外伤害。可是,在大多数的跌倒检测系统中,人们仅利用加速度计设计检测系统,基于单一数据的算法不能完整表征跌倒时身体姿态变化的信息。为此本文拟采用陀螺仪和加速度计的数据设计跌倒检测的算法。方法 首先介绍了利用MEMS惯性传感器设计置于腰间的可穿戴的跌倒检测系统,然后对跌倒的规律进行了分析,基于此提出了基于多传感器数据融合的跌倒检测算法,即通过数据融合的技术提取出身体加速度及其动态量和静态量、加速度变化量、身体姿态角、角速度绝对值之和等特征参数,利用多参数设计了基于阈值判定的跌倒检测算法。结果 收集10名志愿者做模拟跌倒以及日常活动的数据,对算法的有效性进行验证,取得96.67%的灵敏度和97%的特异性,并且此指标高于Kagans等算法的结果。结论 本文提出的算法在跌倒检测中具有较好的有效性及优点。

Objective Fall, a common phenomenon, remains a major source of morbidity and mortality among older adults. Real-time detection system of falls can alarm in time when falling happens, shorten the waiting time for treatment to reduce injuries caused by a fall. In most of the fall detection systems, however, people only employ accelerometer to design detection systems so that these algorithms do not completely demonstrate the characteristic of falling. So this paper uses gyroscope and accelerometer sensors to devise the algorithm. Methods This study, firstly, designs a wearable fall detection system on the waist by using the MEMS inertial sensors. Secondly, according to the law of fall, this study proposes a fall detection algorithm based on multi-sensor data fusion, which extracts the body acceleration and its dynamic and static parameter, the body attitude angle, the absolute values of angular velocity. Third, a fall detection algorithm is designed based on multi-sensor data by using the parameters. Results We evaluate the algorithm on data recorded from 10 volunteers performing falls and activities of daily living (ADL), achieving 96.67% sensitivity and 97% specificity, superior to the algorithm reported by Kagans et al. Conclusions  The algorithm based on multi-sensor data fusion is a more suitable method of fall-detection.

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