College - Author 1

College of Engineering

Department - Author 1

Electrical Engineering Department

Degree Name - Author 1

BS in Electrical Engineering



Primary Advisor

Xiao-Hua Yu


There is a growing desire to understand the EEG (electroencephalogram) signals related with brain activities. In order to analyze EEG signals, they first must be measured by sensors, which induces a lot of noise; then these signals are classified to understand the intended actions. In many cases a neural network is used as the algorithms for classification. A residual neural network (ResNet) is an artificial neural network (ANN) of a kind that are related with the pyramidal cells in the cerebral cortex. The goal of this work is to investigate the viability of ResNets for classifying EEG signals for hand motor movement, and compare its performance with other neural network models such as ConvNets.

Available for download on Friday, June 14, 2024