Detection of pre movement event-related desynchronization from single trial EEG signal

Karthik Soman; Prabhav Reddy; Heba Lakany

doi:10.1109/CICT.2013.6558201

Detection of pre movement event-related desynchronization from single trial EEG signal

Karthik Soman, Prabhav Reddy, Heba Lakany

Biomedical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

Abstract

Brain Computer Interfacing provides a new of communication for the paralyzed persons affected with Amyotrophic Lateral Sclerosis, Spinal Cord Injury or Brain stem stroke. Detection of the occurrence of the events from the EEG signal from a single trial forms the basis for the real time implementation of BCI. The stochastic nature of EEG signal makes it a challenging one. This paper proposes a method by which event detection was done from a single trial of EEG signal by detecting the Mu Band ERD. The proposed method was compared with the conventional method for quantifying ERD. The statistical analysis using t test proved that at a confidence level of 95%, the proposed method detects the ERD occurrence time within a range of 90% of the conventional method.

Original language	English
Title of host publication	2013 IEEE Conference on Information & Communication Technologies
Place of Publication	Piscataway
Publisher	IEEE
Pages	788-792
Number of pages	5
ISBN (Print)	9781467357593
DOIs	https://doi.org/10.1109/CICT.2013.6558201
Publication status	Published - 15 Jul 2013

Keywords

electroencephalography
adaptive filters
band-pass filters
fintie impulse response filters
electrodes
electrooculography
brain computer interface
amyotrophic lateral sclerosis
mu band
EEG
ERD

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10.1109/CICT.2013.6558201

Karthik Soman
Lakany, H. (Host) & Conway, B. (Host)
12 Jul 2012 → 28 Sept 2012
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Cite this

@inproceedings{da9076c19cbd464a8de785f74f1f52b1,

title = "Detection of pre movement event-related desynchronization from single trial EEG signal",

abstract = "Brain Computer Interfacing provides a new of communication for the paralyzed persons affected with Amyotrophic Lateral Sclerosis, Spinal Cord Injury or Brain stem stroke. Detection of the occurrence of the events from the EEG signal from a single trial forms the basis for the real time implementation of BCI. The stochastic nature of EEG signal makes it a challenging one. This paper proposes a method by which event detection was done from a single trial of EEG signal by detecting the Mu Band ERD. The proposed method was compared with the conventional method for quantifying ERD. The statistical analysis using t test proved that at a confidence level of 95%, the proposed method detects the ERD occurrence time within a range of 90% of the conventional method.",

keywords = "electroencephalography, adaptive filters, band-pass filters, fintie impulse response filters, electrodes, electrooculography, brain computer interface, amyotrophic lateral sclerosis, mu band, EEG, ERD",

author = "Karthik Soman and Prabhav Reddy and Heba Lakany",

year = "2013",

month = jul,

day = "15",

doi = "10.1109/CICT.2013.6558201",

language = "English",

isbn = "9781467357593",

pages = "788--792",

booktitle = "2013 IEEE Conference on Information & Communication Technologies",

publisher = "IEEE",

}

TY - GEN

T1 - Detection of pre movement event-related desynchronization from single trial EEG signal

AU - Soman, Karthik

AU - Reddy, Prabhav

AU - Lakany, Heba

PY - 2013/7/15

Y1 - 2013/7/15

N2 - Brain Computer Interfacing provides a new of communication for the paralyzed persons affected with Amyotrophic Lateral Sclerosis, Spinal Cord Injury or Brain stem stroke. Detection of the occurrence of the events from the EEG signal from a single trial forms the basis for the real time implementation of BCI. The stochastic nature of EEG signal makes it a challenging one. This paper proposes a method by which event detection was done from a single trial of EEG signal by detecting the Mu Band ERD. The proposed method was compared with the conventional method for quantifying ERD. The statistical analysis using t test proved that at a confidence level of 95%, the proposed method detects the ERD occurrence time within a range of 90% of the conventional method.

AB - Brain Computer Interfacing provides a new of communication for the paralyzed persons affected with Amyotrophic Lateral Sclerosis, Spinal Cord Injury or Brain stem stroke. Detection of the occurrence of the events from the EEG signal from a single trial forms the basis for the real time implementation of BCI. The stochastic nature of EEG signal makes it a challenging one. This paper proposes a method by which event detection was done from a single trial of EEG signal by detecting the Mu Band ERD. The proposed method was compared with the conventional method for quantifying ERD. The statistical analysis using t test proved that at a confidence level of 95%, the proposed method detects the ERD occurrence time within a range of 90% of the conventional method.

KW - electroencephalography

KW - adaptive filters

KW - band-pass filters

KW - fintie impulse response filters

KW - electrodes

KW - electrooculography

KW - brain computer interface

KW - amyotrophic lateral sclerosis

KW - mu band

KW - EEG

KW - ERD

U2 - 10.1109/CICT.2013.6558201

DO - 10.1109/CICT.2013.6558201

M3 - Conference contribution book

SN - 9781467357593

SP - 788

EP - 792

BT - 2013 IEEE Conference on Information & Communication Technologies

PB - IEEE

CY - Piscataway

ER -

Detection of pre movement event-related desynchronization from single trial EEG signal

Abstract

Keywords

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