Elderly safety: A smartphone based real time approach

Abstract

As the number of elderly people living worldwide and average life expectancy increases, older adults' safety assurance has become increasingly important. There are many works on safety issues of the elderly focusing on human activity classification. Most of them use external sensor devices and/or completely or partially user input based classification and prediction systems. In this paper, we have developed an algorithmic model, monitored and documented elderly people's daily activities by using the gyroscope and accelerometer of a smartphone and with the use of those data and model, we calculated how much activity is required or overdone for a subject in order to maintain a healthy lifestyle. More importantly, we built a real time system that could not only judge what basic activity the subject is currently doing, but also protect the subject from possible injury that might happen to the subject if abnormal data is received. © 2013 Springer-Verlag Berlin Heidelberg.