Fall Detection Using Smartphones to Enhance Safety and Security of Older Adults at Home

Abstract

Falling is a global common health problem among older adults which causes minor to serious injuries such as fracture or even death. In recent years, many falls detection systems have been developed to support early detection and timely care to eliminate grave consequences. This research evaluates the potential of using smartphones for fall detection. In this research, two smartphones were used to collect acceleration data. Threshold approaches were applied on the collected data to detect potential falls. Evaluation results show that with proper chosen thresholds, the tested fall detection algorithm performs well with both sensitivity and specificity.