Comparing EEG patterns of actual and imaginary wrist movements - a machine learning approach

Lakany, H. and Conway, B.A. (2005) Comparing EEG patterns of actual and imaginary wrist movements - a machine learning approach. Proceedings of the first ICGST International Conference on Artificial Intelligence and Machine Learning AIML 05 . ICGST, Cairo, Egypt. ISBN 21968/2005

[thumbnail of strathprints008376]
Preview
 Text. Filename: strathprints008376.pdf
Accepted Author Manuscript
Download (283kB)| Preview

    Abstract

    Our goal is to develop an algorithm for feature extraction and classification to be used in building brain-computer interfaces. In this paper, we present preliminary results for classifying EEG data of imaginary wrist movements. We have developed an algorithm based on the spatio-temporal features of the recorded EEG signals. We discuss the differences between the feature vectors selected for both actual and imaginary wrist movements and compare classification results.

    ORCID iDs

    Lakany, H. ORCID logoORCID: https://orcid.org/0000-0003-3079-0392 and Conway, B.A. ORCID logoORCID: https://orcid.org/0000-0002-0069-0131;
    CORE (COnnecting REpositories)