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Intelligent Sensor Floor for Fall Prediction and Gait Analysis *
| Content Provider | Semantic Scholar |
|---|---|
| Author | Jideofor, Valentine Young, Christina Manfred Huber Zaruba, Gergely |
| Copyright Year | 2013 |
| Abstract | Falls account for a significant number of injury and death in the elderly. Risk factors for falls include increase in muscle weakness, change in gait and balance abnormalities. Detecting these changes are an important part of a smart health and aging environment. Because fall assessments do not occur very often, usually once a year in a patient's annual physical, there is a need to develop a system that can monitor and assess gait and balance more periodically. This will allow older adults to continue living in an independent setting and reduce the need for expensive care facilities. The objective of this project is to use gait analysis to accurately predict and detect anomalous behavior and help predict fall and health issues particularly in elderly persons. This paper describes the investigation and development of the Intelligent Sensor Floor used for gait and balance analysis. It can be used to monitor and assess fall risk in the home environment in an unobtrusive way. We will describe the hardware, circuit and floor construction process, sensor calibration, and initial data collection. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://cse.uta.edu/research/Publications/CSE-2012-4.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
