Title :
Foot gait time series estimation based on support vector machine
Author :
Pant, Jeevan ; Krishnan, Sridhar
Author_Institution :
Dept. of Electr. & Comput. Eng., Ryerson Univ., Toronto, ON, Canada
Abstract :
A new algorithm for the estimation of stride interval time series from foot gait signals is proposed. The algorithm is based on the detection of beginning of heel strikes in the signal by using the support vector machine. Morphological operations are used to enhance the accuracy of detection. By taking backward differences of the detected beginning of heel strikes, stride interval time series is estimated. Simulation results are presented which shows that the proposed algorithm yields fairly accurate estimation of stride interval time series where estimation error for mean and standard deviation of the time series is of the order of 10-4.
Keywords :
gait analysis; support vector machines; time series; foot gait time series estimation; heel strikes; morphological operations; stride interval time series; support vector machine; Estimation; Foot; Standards; Support vector machines; Time series analysis; Training; Vectors;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE
Conference_Location :
Chicago, IL
DOI :
10.1109/EMBC.2014.6945095