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摘要:
Automated falling detection is one of the important tasks in this ageing society. Such systems are supposed to have little interference on daily life. Doppler sensors have come to the front as useful?devices to detect human activity without using any wearable sensors. The conventional Doppler sensor based falling detection mechanism uses the features of only one sensor. This paper presents falling detection using multiple Doppler sensors. The resulting data from sensors are combined or selected to find out the falling event. The combination method, using three sensors, shows 95.5% accuracy of falling detection. Moreover, this method compensates the drawbacks of mono Doppler sensor which encounters problems when detecting movement orthogonal to irradiation directions.
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惰性基质燃料元件 Doppler系数分析
惰性基质燃料
Doppler系数
蒙特卡罗模拟
内容分析
关键词云
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文献信息
篇名 Learning Based Falling Detection Using Multiple Doppler Sensors
来源期刊 物联网(英文) 学科 医学
关键词 FALLING DETECTION DOPPLER Sensor CEPSTRUM Analysis SVM K-NN
年,卷(期) 2013,(2) 所属期刊栏目
研究方向 页码范围 33-43
页数 11页 分类号 R73
字数 语种
DOI
五维指标
传播情况
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研究主题发展历程
节点文献
FALLING
DETECTION
DOPPLER
Sensor
CEPSTRUM
Analysis
SVM
K-NN
研究起点
研究来源
研究分支
研究去脉
引文网络交叉学科
相关学者/机构
期刊影响力
物联网(英文)
季刊
2161-6817
武汉市江夏区汤逊湖北路38号光谷总部空间
出版文献量(篇)
78
总下载数(次)
0
总被引数(次)
0
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