Publications
2016
Wairagkar, Maitreyee; Daly, Ian; Hayashi, Yoshikatsu; Nasuto, Slawomir
Autocorrelation based EEG Dynamics depicting Motor Intention Conference
BCI Meeting 2016, 2016.
BibTeX | Tags: Autocorrelation, BCI, Classification, EEG, ERD
@conference{Wairagkar2016,
title = {Autocorrelation based EEG Dynamics depicting Motor Intention },
author = {Maitreyee Wairagkar and Ian Daly and Yoshikatsu Hayashi and Slawomir Nasuto},
year = {2016},
date = {2016-06-01},
booktitle = {BCI Meeting 2016},
keywords = {Autocorrelation, BCI, Classification, EEG, ERD},
pubstate = {published},
tppubtype = {conference}
}
2014
Wairagkar, Maitreyee; Daly, Ian; Hayashi, Yoshikatsu; Nasuto, Slawomir
Novel single trial movement classification based on temporal dynamics of EEG Conference
Proceedings of the Graz Brain-computer interface conference 2014, 2014.
Abstract | Links | BibTeX | Tags: Autocorrelation, BCI, Classification, EEG, ERD, Motor imagery
@conference{Wairagkar2014,
title = {Novel single trial movement classification based on temporal dynamics of EEG},
author = {Maitreyee Wairagkar and Ian Daly and Yoshikatsu Hayashi and Slawomir Nasuto},
url = {http://centaur.reading.ac.uk/37412/1/Graz%20conference%202014-Final%20version.pdf},
year = {2014},
date = {2014-09-01},
booktitle = {Proceedings of the Graz Brain-computer interface conference 2014},
abstract = {Various complex oscillatory processes are involved in the generation of the motor command. The temporal dynamics of these processes were studied for movement detection from single trial electroencephalogram (EEG). Autocorrelation analysis was performed on the EEG signals to find robust markers of movement detection. The evolution of the autocorrelation function was characterised via the relaxation time of the autocorrelation by exponential curve fitting. It was observed that the decay constant of
the exponential curve increased during movement, indicating that the autocorrelation function decays slowly during motor execution. Significant differences were observed between movement and no moment tasks. Additionally, a linear discriminant analysis (LDA) classifier was used to identify movement trials with a peak accuracy of 74%. },
keywords = {Autocorrelation, BCI, Classification, EEG, ERD, Motor imagery},
pubstate = {published},
tppubtype = {conference}
}
Various complex oscillatory processes are involved in the generation of the motor command. The temporal dynamics of these processes were studied for movement detection from single trial electroencephalogram (EEG). Autocorrelation analysis was performed on the EEG signals to find robust markers of movement detection. The evolution of the autocorrelation function was characterised via the relaxation time of the autocorrelation by exponential curve fitting. It was observed that the decay constant of
the exponential curve increased during movement, indicating that the autocorrelation function decays slowly during motor execution. Significant differences were observed between movement and no moment tasks. Additionally, a linear discriminant analysis (LDA) classifier was used to identify movement trials with a peak accuracy of 74%.
the exponential curve increased during movement, indicating that the autocorrelation function decays slowly during motor execution. Significant differences were observed between movement and no moment tasks. Additionally, a linear discriminant analysis (LDA) classifier was used to identify movement trials with a peak accuracy of 74%.