dc.contributor.author | Gonzales, Ian James Daniel | |
dc.date.accessioned | 2011-10-11T11:39:42Z | |
dc.date.available | 2011-10-11T11:39:42Z | |
dc.date.issued | 2011 | |
dc.identifier.uri | http://hdl.handle.net/11250/144142 | |
dc.description.abstract | A working fall detection system is of medical interest and significance for people who has risk of falling, their family, healthcare workers and the entire health care community. We always say that prevention is better than cure or treatment. This is also true for falling, and that is why fall prevention research and studies are very important. Ultimately though, we cannot prevent all falls! As such, the next best thing is an immediate response and assistance for the person who fell and possibly injured himself. This paper is a study of fall detection systems. We will take an academic view on what they are and their nature as an assistive tool. We will make our own fall detection system using a smartphone as the device platform. Three specific accelerometer-based algorithms will be tested and compared to each other. By the end of the study, we will present a prototype of our system and its performance. | en_US |
dc.language.iso | eng | en_US |
dc.subject | mediatechnology | en_US |
dc.subject | fall detection system | en_US |
dc.title | Fall Detection Using a Smartphone | en_US |
dc.type | Master thesis | en_US |
dc.subject.nsi | VDP::Mathematics and natural science: 400::Information and communication science: 420::System development and system design: 426 | en_US |
dc.source.pagenumber | XIII, 106 s. | en_US |