Real time ocular and facial muscle artifacts removal from EEG signals using LMS adaptive algorithm

Mehrkanoon, S. and Moghavvemi, M. and Fariborzi, H. (2007) Real time ocular and facial muscle artifacts removal from EEG signals using LMS adaptive algorithm. In: 2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007, 25 - 28 November 2007, Kuala Lumpur, Malaysia.

Full text not available from this repository.

Abstract

The EEG signal is most useful for clinical diagnosis and in biomedical research. ElectroOculoGram (EOG), ElectroMyoGram (EMG) artifact are produced by eye movement and facial muscle movement respectively. An adaptive filtering method is proposed to remove these artifacts signals from EEG signals. Proposed method uses horizontal EOG (HEOG), vertical EOG (VEOG), and EMG signals as three reference digital filter inputs. The real-time artifact removal is implemented by multi-channel Least Mean Square algorithm. The resulting EEG signals display an accurate and artifact free feature.

Item Type: Conference or Workshop Item (Paper)
Additional Information: ISBN: 1424413559;978-142441355-3 DOI: 10.1109/ICIAS.2007.4658583
Uncontrolled Keywords: EEG; EMG; EOG; Finite Impulse Response; Least Mean Square; Noise cancellation; Real-time -adaptive filter; EEG; EMG; EOG; Finite Impulse Response; Least Mean Square; Noise cancellation; Real-time -adaptive filter;
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Engineering
Depositing User: Ms. Norhamizah Tamizi
Date Deposited: 25 Mar 2014 08:34
Last Modified: 23 Nov 2017 02:01
URI: http://eprints.um.edu.my/id/eprint/9723

Actions (login required)

View Item View Item