NDLI: Upper limb EMG artifact rejection in motor sensitive BCIs

Content Provider	IEEE Xplore Digital Library
Author	Murguialday, A.R. Soares, E. Birbaumer, N.
Copyright Year	2010
Description	Author affiliation: Institute of Medical Psychology and Behavioral Neurobiology and MEG Center, Germany (Murguialday, A.R.; Soares, E.; Birbaumer, N.)
Abstract	Motor imagery-based brain computer interface (BCI) technologh has mototor rehabilitation as one of its main fields of application. The use of a BCI as a neuroprosthetic for paralyzed limb motor restoration implies normally absence of muscle activity. It is still an open question whether residual motor activity in healthy individuals or in patients causes a bias in the modulation of a motor imagery-based BCI control signal. Although the influence of electromyographical (EMG) activity in necka nd cranial muscles upon BCI has been studied, not much has been said concerning the revelance of EMG activity arising from arm muscles. We therefore used a hand motor imagery-based BCI system paradigm designed for motor rehabilitation coupling a BCI with an online driven robotic orthosis to compare different EMG activity detection methods regarding their influence in the resulting analysis of neurophysiological signals. Fourteen healthy subjects underwent four sessions in which they were asked to perform motor imagery task alone (receiving no feedback), motor imagery with (visual and proprioceptive)feedback, active movement, passive movement and rest. Six different EMG feature extraction methods were calculated and three different data time windows were used for muscle activity threshold definition. Three different electrode spatial distributions were utilized for removing the EMG artifacts: a) coming from all the electrodes on the arms, b) just the ones placed on the imagery side and c) just the ones on the healthy arm. We compared the different EMG rejection methods by calculating the number of trials deemed artifact-free by each method. In this paper we demonstrate that different EMG artifact removal methods lead to distinct partitions of the total available data, thus yielding different influence of the method used to remove EMG artifacts on task related artifacts regarding number of trials contaminated and the differences in trials rejected using the different methods.
Starting Page	1
Ending Page	6
File Size	9490565
Page Count	6
File Format	PDF
ISBN	9781424441235
ISSN	1557170X
DOI	10.1109/IEMBS.2010.5735240
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-31
Publisher Place	Argentina
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electromyography Muscles Electrodes Feature extraction Brain computer interfaces Electroencephalography Fingers
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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