Automatic Gait Balance Detection System
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Authors
Pallis, Jani M.
Shah, Parth
Faezipour, Miad
Issue Date
2017-03-24
Type
Presentation
Language
en_US
Keywords
Detection , Fall detection , Mobile application
Alternative Title
Abstract
Falls are one of the major causes of injury in elderly people over 65 years. Each year, 2.5 million people are treated for a serious fall injury. In addition to the fall there is the delay in receiving assistance. Researchers have developed three methodologies to detect falls: image/video processing by implementing cameras and trackers, acoustic recognition using floor and wall sensors and by analysis of wearable sensors. Fall detection using smartphones has also been proposed in the past. A smartphone may have many constraints due to which a wearable device is a much more viable option for such a critical issue. This poster aims to suggest an effective way to detect falls by using a wearable device of which the major components are: 3-axial accelerometer, Arduino Uno, and GPS-GSM device. Apart from that, a buzzer is also integrated to notify people nearby for assistance. The location of the wearable device also affects the acceleration and the result of fall and motion detection. Although the wrist is the most common body part for any wearable device, the acceleration signal may vary widely. It is efficient to place the device in areas of least movement like a knee or waist.