Gait cycle analysis in transtibial amputees and non-amputees using kinect camera

This project consists in the analysis of the gait cycle of amputees and non-amputees through the use of kinect cameras with the aim of studying the different biomechanical variables so that the design of protheses (including sockets) for amputees can be improved to ameliorate their life quality. The project is developed around the following points:

Design of an algorithm for electromyography (EMG) signals classification

This project analyzes 25 electromyographic signals, obtained from the posterior forearm region of healthy people, which were digitally processed to extract particular features, including the average, maximum, minimum, standard deviation, ABC, Fourier harmonics, RMS signal, and wave length. These features are processed to classify the signals into five movements stated as classes.