Impact of different walking surfaces on gait identification based on higher-order statistics of accelerometer data

This paper presents an investigation on how different walking surfaces affect gait identification based on accelerometer data. Accelerometer data of 5 subjects walking on 4 different solid surfaces was acquired on 3 different days by a cell phone placed on the subject´s hip. Data analysis detects gait cycles by a method based on wavelet transform. For all gait cycles, features were calculated by using higher-order statistics. Similarity estimation for discerning the different subjects and surfaces was introduced by using principal component analysis (PCA). It proved that the different solid surfaces do not influence the efficiency of the identification of subjects based on their gait.