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A Wrist-Type Fall Detector with Statistical Classifier for the Elderly Care
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- Authors
- Chankyu Park, Jaehong Kim, Joo-chan Sohn, Ho-Jin Choi
- Issue Date
- 2011-10
- Citation
- KSII Transactions on Internet and Information Systems, v.5, no.10, pp.1751-1769
- ISSN
- 1976-7277
- Publisher
- 한국인터넷정보학회
- Language
- English
- Type
- Journal Article
- Abstract
- 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 Keywords
- Classification Performance, Data sets, Elderly Care, Elderly People, Fall Detection, Positive results, Statistical classifier, User Requirements, detection techniques, the body