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http://hdl.handle.net/11375/14434
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DC Field | Value | Language |
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dc.contributor.author | Nguyen, Binh | en_US |
dc.contributor.author | Tomkun, Jonathan | en_US |
dc.date.accessioned | 2014-06-18T18:13:18Z | - |
dc.date.available | 2014-06-18T18:13:18Z | - |
dc.date.created | 2011-02-18 | en_US |
dc.date.issued | 2010-04-23 | en_US |
dc.identifier.other | ee4bi6/33 | en_US |
dc.identifier.other | 1060 | en_US |
dc.identifier.other | 1797071 | en_US |
dc.identifier.uri | http://hdl.handle.net/11375/14434 | - |
dc.description.abstract | <p>In the elderly population, falls are amongst the most frequent and dangerous causes of accidental injuries. It is estimated that more than 1 in 3 persons over the age of 65 are victims to falls each year[4][6]. Proceeding an accidental fall victims are often injured or immobilized. In the elderly population over 72 years of age, approximately 47% of the injured victims are unable to regain upright stance[9]. Without assistance, fallers often remain on the ground. Long-lie is the term used to describe fall-induced immobilization of victims for extended durations of time[7]. In 2004 it was estimated that 20% of fall-induced hospitalizations were associated with Long-lie[11]. In the same statistical report, Long-lie following a fall-induced injury is closely linked to cases of mortality amongst the elderly[11]. An automated system that can reduce duration of fall- induced Long-lie or even frequency of falls will therefore be greatly beneficial. The objective of this project is to engineer a fall-detection system that will i) accurately detect a fall, ii) prevent falls if possible by alerting the user of unstable physical orientations and iii) send out a distress signal to a handheld device or other communication devices wirelessly. The device is to be a compact unit worn around the waist and will communicate wirelessly via Bluetooth.</p> | en_US |
dc.subject | Biomedical | en_US |
dc.subject | Electrical and Computer Engineering | en_US |
dc.subject | Biomedical | en_US |
dc.title | Hybrid System for Fall Detection & Fall Prevention | en_US |
dc.type | capstone | en_US |
Appears in Collections: | EE 4BI6 Electrical Engineering Biomedical Capstones |
Files in This Item:
File | Size | Format | |
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fulltext.pdf | 3.24 MB | Adobe PDF | View/Open |
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