EEG-Based Movement Imagery Classification Using Machine Learning Techniques and Welch’s Power Spectral Density Estimation


  • Saman Sarraf Department of Electrical and Computer Engineering, McMaster University, Hamilton, Ontario, Canada, The Institute of Electrical and Electronics Engineers, IEEE


EEG, Machine Learning, Movement Imagery.


This project implements an EEG-based movement imagery classification using Welch’s Power Spectral Density estimation which could be used in Brain Computer Interface systems.  This classification which is based on the extracted features from


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How to Cite

Sarraf, S. (2017). EEG-Based Movement Imagery Classification Using Machine Learning Techniques and Welch’s Power Spectral Density Estimation. American Scientific Research Journal for Engineering, Technology, and Sciences, 33(1), 124–145. Retrieved from