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학술지 A Wrist-Type Fall Detector with Statistical Classifier for the Elderly Care
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저자
박찬규, 김재홍, 손주찬, 최호진
발행일
201110
출처
KSII Transactions on Internet and Information Systems, v.5 no.10, pp.1751-1769
ISSN
1976-7277
출판사
한국인터넷정보학회
DOI
https://dx.doi.org/10.3837/tiis.2011.10.004
협약과제
11MC2700, 인간-로봇 상호작용 매개 기술 개발, 김재홍
초록
Falls are one of the most concerned accidents for elderly people and often result in serious physical and psychological consequences. Many researchers have studied fall detection techniques in various domain, however none released to a commercial product satisfying user requirements. We present a systematic modeling and evaluating procedure for best classification performance and then do experiments for comparing the performance of six procedures to get a statistical classifier based wrist-type fall detector to prevent dangerous consequences from falls. Even though the wrist may be the most difficult measurement location on the body to discern a fall event, the proposed feature deduction process and fall classification procedures shows positive results by using data sets of fall and general activity as two classes. © 2011 KSII.
KSP 제안 키워드
Classification Performance, Data sets, Elderly Care, Elderly People, Fall Detection, Positive results, Statistical classifier, User Requirements, detection techniques, the body