Citation

Silapachote P, Srisuphab A, Phongpawarit J, Visetpalitpol S, Jirapasitchai S. ECTI Trans. Comput. Info. Technol. 2017; 10(2): 185-195.

Copyright

(Copyright © 2017, ECTI Association, Sirindhon International Institute of Technology)

DOI

unavailable

PMID

unavailable

Abstract

Caring for a rapid and ever-increasing older population, providing social support and monitoring emotional wellness, is the most immediate and most urgent challenge prompted by the global aging of baby boomers. Elderly assisted systems do not only promote independent lifestyles, enhancing their quality of life, but also reduce stress and worry of families and friends. While being physically active is beneficial and much encouraged, it does increase the risk of falls. We developed an affordable fall detection and response tracking application on the cloud platform; mobile cloud computing is a major evolution with rising impact in information technology and enterprises. Our system, named REDLE, features push notifications for fall alerts and real-time maps for tracking and providing locations and phone numbers of nearby hospitals. Implemented on Android, it captures signals from an embedded tri-axial accelerometer and a global positioning system sensor. Coupled with an efficient threshold-based fall detection algorithm for instantaneous responses, REDLE achieved a near perfect fall detection rate and accurate tracking. Users enjoyed the smoothness of our interactive interface, and complimented on its ease of use and familiarity.

Language: en