Delta band contribution in cue based single trial classification of real and imaginary wrist movements

Vuckovic, A. and Sepulveda, F. (2008) Delta band contribution in cue based single trial classification of real and imaginary wrist movements. Medical and Biological Engineering and Computing, 46(6), pp. 529-539. (doi: 10.1007/s11517-008-0345-8)

Abstract

The aim of this study was to classify different movements about the right wrist. Four different movements were performed: extension, flexion, pronation and supination. Two-class single trial classification was performed on six possible combinations of two movements (extension-flexion, extension-supination, extension-pronation, flexion-supination, flexion-pronation, pronation-supination). Both real and imaginary movements were analysed. The analysis was done in the joint time-frequency domain using the Gabor transform. Feature selection was based on the Davis-Bouldin Index (DBI) and feature classification was based on Elman's recurrent neural networks (ENN). The best classification results, near 80% true positive rate, for imaginary movements were achieved for discrimination between extension and any other type of movement. The experiments were run with 10 able-bodied subjects. For some subjects, real movement classification rates higher than 80% were achieved for any combination of movements, though not simultaneously for all six combinations of movements. For classification of the imaginary movements, the results suggest that the type of movement and frequency band play an important role. Unexpectedly, the delta band was found to carry significant class-related information.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Vuckovic, Dr Aleksandra
• Authors: Vuckovic, A., and Sepulveda, F.
• Subjects: R Medicine > R Medicine (General); T Technology > T Technology (General)
• College/School: College of Science and Engineering > School of Engineering > Biomedical Engineering
• Journal Name: Medical and Biological Engineering and Computing
• ISSN: 0140-0118