Using a foot mounted accelerometer to detect changes in gait patterns.

The purpose of this study is to investigate how data from a foot mounted accelerometer can be used to detect motor pattern healthy subjects performed walking trails under two different conditions; normal and stiff ankle walking. Lower body kinematic data were collected as well as accelerometer data from both feet. An algorithm is presented which quantifies relevant swing phase characteristics from the foot accelerometer. Peak total acceleration during initial swing was significantly higher in the stiff ankle condition (M = 33.10, SD = 5.12) than in the normal walking condition (M = 29.47, SD = 5.75; t(7) = 4.32, p = .003, two-tailed). There was a large effect size (eta squared = 0.853). Time between peak acceleration during initial swing to foot strike was significantly shorter in the stiff ankle condition (M = 0.42, SD = 0.02) than in the normal condition (M = 0.44, SD = 0.03; t(7) = -2.54, p = .039, two- tailed). There was a large effect size (eta squared = 0.693). Simple to process metrics from tri-axial accelerometer data on the foot show potential to detect changes in ankle kinematic patterns.