title   
  

Detection of intention level in response to task difficulty from EEG signals

Koyaş, Ela and Hocaoğlu, Elif and Patoğlu, Volkan and Çetin, Müjdat (2013) Detection of intention level in response to task difficulty from EEG signals. In: IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2013), Southampton, UK

[img]
Preview
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
7Mb

Official URL: http://dx.doi.org/10.1109/MLSP.2013.6661905

Abstract

We present an approach that enables detecting intention levels of subjects in response to task difficulty utilizing an electroencephalogram (EEG) based brain-computer interface (BCI). In particular, we use linear discriminant analysis (LDA) to classify event-related synchronization (ERS) and desynchronization (ERD) patterns associated with right elbow flexion and extension movements, while lifting different weights. We observe that it is possible to classify tasks of varying difficulty based on EEG signals. Additionally, we also present a correlation analysis between intention levels detected from EEG and surface electromyogram (sEMG) signals. Our experimental results suggest that it is possible to extract the intention level information from EEG signals in response to task difficulty and indicate some level of correlation between EEG and EMG. With a view towards detecting patients' intention levels during rehabilitation therapies, the proposed approach has the potential to ensure active involvement of patients throughout exercise routines and increase the efficacy of robot assisted therapies.

Item Type:Papers in Conference Proceedings
Uncontrolled Keywords:EEG, BCI, LDA, sEMG, intention level, robotic rehabilitation
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
ID Code:23481
Deposited By:Müjdat Çetin
Deposited On:13 Jan 2014 12:52
Last Modified:13 Jan 2014 12:52

Repository Staff Only: item control page