Walking-Age Analyzer for Healthcare Applications

This paper describes a walking-age pattern analysis and identification system using a 3-D accelerometer and a gyroscope. First, a walking pattern database from 79 volunteers of ages ranging from 10 to 83 years is constructed. Second, using feature extraction and clustering, three distinct walking-age groups, children of ages 10 and below, adults in 20-60s, and elders in 70s and 80s, were identified. For this study, low-pass filtering, empirical …