2010 · 236 citations · 14 references
ComputingHealth InformaticsInformation TechnologyMobile ComputingMobile Health InformaticsMobile SystemsFall DetectionFall RiskMobile Application DevelopmentMobile Health ApplicationsMobile Human-computer InteractionMobile SensingElderly PopulationFall Detection SystemsFall RecognitionHealth Risk IdentificationPower EfficiencyPrototype Evaluation
Falls are a major health risk that diminish the quality of life among elderly people. With the elderly population surging, especially with aging “baby boomers”, fall detection becomes increasingly important. However, existing commercial products and academic solutions struggle to achieve pervasive fall detection. In this paper, we propose utilizing mobile phones as a platform for pervasive fall detection system development. To our knowledge, we are the first to do so. We design a detection algorithm based on mobile phone platforms. We propose PerFallD, a pervasive fall detection system implemented on mobile phones. We implement a prototype system on the Android G1 phone and conduct experiments to evaluate our system. In particular, we compare PerFallD's performance with that of existing work and a commercial product. Experimental results show that PerFallD achieves strong detection performance and power efficiency.
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Dean M. Karantonis, Michael R. Narayanan, M. Mathie et al. · IEEE Transactions on Information Technology in Biomedicine · 2006 · 1.2K citations
Engineering, Health Informatics, Mechatronics Engineering +17
Wearable Sensors for Reliable Fall Detection
J. Chen, K. K. Kwong, David C. Chang et al. · 2005 · 447 citations