Acoustic Gaits: Gait Analysis With Footstep Sounds

摘要

We describe the acoustic gaits—the natural human gait quantitative characteristics derived from the sound of footsteps as the person walks normally. We introduce the acoustic gait profile, which is obtained from temporal signal analysis of sound of footsteps collected by microphones and illustrate some of the spatio-temporal gait parameters that can be extracted from the acoustic gait profile by using three temporal signal analysis methods—the squared energy estimate, Hilbert transform and Teager–Kaiser energy operator. Based on the statistical analysis of the parameter estimates, we show that the spatio-temporal parameters and gait characteristics obtained using the acoustic gait profile can consistently and reliably estimate a subset of clinical and biometric gait parameters currently in use for standardized gait assessments. We conclude that the Teager–Kaiser energy operator provides the most consistent gait parameter estimates showing the least variation across different sessions and zones. Acoustic gaits use an inexpensive set of microphones with a computing device as an accurate and unintrusive gait analysis system. This is in contrast to the expensive and intrusive systems currently used in laboratory gait analysis such as the force plates, pressure mats and wearable sensors, some of which may change the gait parameters that are being measured.