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Human fall detection on embedded platform using depth maps and wireless accelerometer

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dc.contributor.author Kwolek, Bogdan
dc.contributor.author Kepski, Michal
dc.date.accessioned 2014-12-23T09:24:43Z
dc.date.available 2014-12-23T09:24:43Z
dc.date.issued 2014-12
dc.identifier.citation Bogdan Kwolek, Michal Kepski, Human fall detection on embedded platform using depth maps and wireless accelerometer, Computer Methods and Programs in Biomedicine, Volume 117, Issue 3, December 2014, Pages 489-501, ISSN 0169-2607 pl_PL.UTF-8
dc.identifier.issn 0169-2607
dc.identifier.uri http://repozytorium.ur.edu.pl/handle/item/791
dc.description.abstract Since falls are a major public health problem in an aging society, there is considerable demand for low-cost fall detection systems. One of the main reasons for non-acceptance of the currently available solutions by seniors is that the fall detectors using only inertial sensors generate too much false alarms. This means that some daily activities are erroneously signaled as fall, which in turn leads to frustration of the users. In this paper we present how to design and implement a low-cost system for reliable fall detection with very low false alarm ratio. The detection of the fall is done on the basis of accelerometric data and depth maps. A tri-axial accelerometer is used to indicate the potential fall as well as to indicate whether the person is in motion. If the measured acceleration is higher than an assumed threshold value, the algorithm extracts the person, calculates the features and then executes the SVM-based classifier to authenticate the fall alarm. It is a 365/7/24 embedded system permitting unobtrusive fall detection as well as preserving privacy of the user. pl_PL.UTF-8
dc.description.sponsorship This work has been supported by the National Science Centre(NCN) within the project N N516 483240. pl_PL.UTF-8
dc.language.iso eng pl_PL.UTF-8
dc.publisher Elsevier pl_PL.UTF-8
dc.subject Fall detection pl_PL.UTF-8
dc.subject Depth image analysis pl_PL.UTF-8
dc.subject Assistive technology pl_PL.UTF-8
dc.subject Sensor technology for smart homes pl_PL.UTF-8
dc.title Human fall detection on embedded platform using depth maps and wireless accelerometer pl_PL.UTF-8
dc.type article pl_PL.UTF-8


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