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R&P: An Low-Cost Device-Free Activity Recognition for E-Health
Li, Liyao1; Bai, Rui1; Xie, Binbin1; Peng, Yao1; Wang, Anwen1; Wang, Wei1; Jiang, Bo1; Liang, Jian2; Chen, Xiaojiang1
Source PublicationIEEE ACCESS
Contribution Rank2

Activity recognition is important for taking care of patients and old men especially in e-Health. The activity recognition system without carrying any wearable devices is widely used in our daily life. Current methods employing uneconomical equipment or even dedicated devices lead to cost-inefficiency for large-scale deployments. This paper introduces R&P, a device-free activity recognition system only using cheap radio frequency identification devices (RFID) tags. Based on the analysis of RFID signals, we extract received signal strength fingerprints and phase fingerprints for each activity and synthesize these two kinds of fingerprints to accurately recognize activities. Moreover, we also modify the dynamic time warping (DTW) algorithm and propose T-DTW method to improve the recognition efficiency. We use commercial passive RFID hardware and verify R&Pin three different environments with different targets and six activities. The results demonstrate that our solution can recognize activities with an average accuracy of 87.9%.


KeywordRfid Device-free Rss Phase T-dtw
Indexed BySCI ; EI
WOS IDWOS:000424078700005
EI Accession Number20180604767049
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Affiliation1.Northwest Univ, Sch Informat Sci & Technol, Xian 710127, Shaanxi, Peoples R China;
2.Chinese Acad Sci, State Key Lab Transient Opt & Photon, Xian 710119, Shaanxi, Peoples R China
Recommended Citation
GB/T 7714
Li, Liyao,Bai, Rui,Xie, Binbin,et al. R&P: An Low-Cost Device-Free Activity Recognition for E-Health[J]. IEEE ACCESS,2018,6:81-90.
APA Li, Liyao.,Bai, Rui.,Xie, Binbin.,Peng, Yao.,Wang, Anwen.,...&Chen, Xiaojiang.(2018).R&P: An Low-Cost Device-Free Activity Recognition for E-Health.IEEE ACCESS,6,81-90.
MLA Li, Liyao,et al."R&P: An Low-Cost Device-Free Activity Recognition for E-Health".IEEE ACCESS 6(2018):81-90.
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