Thesis Project

My graduate thesis project was to establish a publicly available set of algorithms for sEMG classification. Part of what my thesis aimed to achieve was to have a heavily documented set of algorithms for sEMG classification that will allow other researchers to utilize the code for prosthetic training or to build upon the algorithms for their own research. The other aim of my thesis was to improve sEMG classification accuracy by utilizing the Kullback–Leibler Divergence (KLD) which has seen success in sound research to separate sound patterns. My thesis concluded that KLD was able improve sEMG movement classification by 5% in movement groups containing over 20 had movement variations.

To view my thesis report please use the following link Thesis

To view the code I developed for my thesis use the following link Thesis Code