Institute of Electrical and Electronics Engineers Inc.;United States: IEEE
摘要:
摘要： We study anomaly detection in a context that considers user trajectories as input and tries to identify anomalies for users following normal routes such as taking public transportation from the workplace to home or vice versa. Trajectories are modeled as a discrete-time series of axis-parallel constraints ("boxes") in the 2-D space. The anomaly can be estimated by considering two trajectories, where one trajectory is the current movement pattern and the other is a weighted trajectory collected from N norms. The proposed system was implemented and evaluated with eight individuals with cognitive impairments. The experimental results showed that recall was 95.0% and precision was 90.9% on average without false alarm suppression. False alarms and false negatives dropped when axis rotation was applied. The precision with axis rotation was 97.6% and the recall was 98.8%. The average time used for sending locations, running anomaly detection, and issuing warnings was in the range of 15.1-22.7 s. Our findings suggest that the ability to adapt anomaly detection devices for appropriate timing of self-alerts will be particularly important. 其他題名： JBHI 其他題名： IEEE J Biomed Health Inform 出版者： United States: IEEE 出版日期： 2014-01 出處： IEEE journal of biomedical and health informatics, 2014-01, Vol.18 (1), p.384-390 資源來源： IEL(IEEE/IET Electronic Library ) 版權： Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Jan 2014 識別號： ISSN: 2168-2194 識別號： ISSN: 2168-2208 識別號： EISSN: 2168-2208 識別號： DOI: 10.1109/JBHI.2013.2271695 識別號： PMID: 24403438 識別號： CODEN: IJBHA9
