Design of a Fall Detection and Prevention System for the Elderly

Abstract

<p>Falling is a serious health issue among the elderly population; it can result in critical injuries like hip fractures. Immobilization caused by injury or unconsciousness means that the victim cannot summon help themselves. With elderly who live alone, not being found for hours after a fall is quite common and drastically increases the significance of fall-induced injuries. With an aging Baby Boomer population, the incidence of falls will only rise in the next few decades. The objective of this project was to design and create a fall detection and prevention system for the elderly. The system consists of a wearable monitoring device that links wirelessly with a laptop. The device is able to accurately distinguish between fall and non-fall. Upon detecting a fall, the device emits a significant warning from the device and through the laptop, alerting others to the user’s fall. The device is also able to recognize dangerous tilt indicative of a fall, at which time the device emits a warning to the user to correct their orientation to minimize the risk of falling. The focus of this project was developing the most successful algorithm for detecting falls and distinguishing them from non-falls. Multiple algorithms based on both accelerometer and gyroscope platforms were examined then combined into hybrid algorithms concentrating on acceleration magnitude and angle change. The process of establishing the most successful algorithm involved rigorous testing and data collection.</p>