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

Karthik Soman, Prabhav Reddy, Heba Lakany

Research output: Chapter in Book/Report/Conference proceedingConference 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.
LanguageEnglish
Title of host publication2013 IEEE Conference on Information & Communication Technologies
Place of PublicationPiscataway
PublisherIEEE
Pages788-792
Number of pages5
ISBN (Print)9781467357593
DOIs
Publication statusPublished - 15 Jul 2013

Fingerprint

Electroencephalography
Brain
Statistical methods
Communication

Keywords

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

Cite this

Soman, K., Reddy, P., & Lakany, H. (2013). Detection of pre movement event-related desynchronization from single trial EEG signal. In 2013 IEEE Conference on Information & Communication Technologies (pp. 788-792). Piscataway: IEEE. https://doi.org/10.1109/CICT.2013.6558201
Soman, Karthik ; Reddy, Prabhav ; Lakany, Heba. / Detection of pre movement event-related desynchronization from single trial EEG signal. 2013 IEEE Conference on Information & Communication Technologies. Piscataway : IEEE, 2013. pp. 788-792
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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.",
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Soman, K, Reddy, P & Lakany, H 2013, Detection of pre movement event-related desynchronization from single trial EEG signal. in 2013 IEEE Conference on Information & Communication Technologies. IEEE, Piscataway, pp. 788-792. https://doi.org/10.1109/CICT.2013.6558201

Detection of pre movement event-related desynchronization from single trial EEG signal. / Soman, Karthik; Reddy, Prabhav; Lakany, Heba.

2013 IEEE Conference on Information & Communication Technologies. Piscataway : IEEE, 2013. p. 788-792.

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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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.

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Soman K, Reddy P, Lakany H. Detection of pre movement event-related desynchronization from single trial EEG signal. In 2013 IEEE Conference on Information & Communication Technologies. Piscataway: IEEE. 2013. p. 788-792 https://doi.org/10.1109/CICT.2013.6558201