Despite significant preventative efforts, falls continue to be a major source of morbidity and mortality among the elderly. Additionally, the fear of falling can be a major obstacle to independent living for otherwise self-sufficient individuals. This fear is significantly heightened in individuals who have sustained a fall and often results in self-imposed restrictions on mobility and exercise, causing weakening in these individuals and further exacerbating the danger. Much time has been spent developing alert systems in an attempt to mitigate these problems. Unfortunately these systems typically involve dedicated monitoring centers and therefore often come with substantial upfront and recurring costs. This thesis proposes a solution to these problems by implementing fall detection and alert capabilities on a smartphone, devices that are quickly becoming ubiquitous in today’s society. This solution has the potential to quell the fears of many elderly people and their families, while allowing them to maintain their independence at little expense. Detailed herein is the process of designing, developing, and validating this fall detection application. The final application was written in Objective-C for iOS and tested on an iPhone.
| Identifer | oai:union.ndltd.org:CALPOLY/oai:digitalcommons.calpoly.edu:theses-2686 |
| Date | 01 March 2016 |
| Creators | Mosley, Connor Lewis |
| Publisher | DigitalCommons@CalPoly |
| Source Sets | California Polytechnic State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Master's Theses |
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