This study explores wavelet decomposition based skewness analysis for walking speed assessment. This has been achieved by using four force sensing resistors attached beneath the foot and one flex sensor attached on ankle. Experimentation is carried out on walking pattern of able individuals and data are collected using data acquiescing set-up and de-noised using Savitzky–Golay filter. De-noised data are then decomposed at different discrete wavelet transform (DWT) levels from where skewness values of approximate coefficient are assessed. Variation of skewness with respect to walking speed has been observed which shows that skewness values are having definite relations with walking speeds at certain DWT levels. Based on these, an algorithm is proposed for walking speed assessment. Experimentation is again carried out to validate the proposed algorithm. Satisfactory result is achieved indicating that assessment of wavelet decomposition based skewness of approximate coefficients may be very useful for walking speed measurement
