dc.contributor.author | Padma Shri, T. K. | |
dc.contributor.author | Sriraam, N. | |
dc.date.accessioned | 2012-08-22T03:47:51Z | |
dc.date.available | 2012-08-22T03:47:51Z | |
dc.date.issued | 2012-02-27 | |
dc.identifier.citation | p. 89-93 | en_US |
dc.identifier.isbn | 978-145771989-9 | |
dc.identifier.uri | http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6178961 | |
dc.identifier.uri | http://dspace.unimap.edu.my/123456789/20725 | |
dc.description | Link to publisher's homepage at http://ieeexplore.ieee.org/ | en_US |
dc.description.abstract | This paper suggests the application of gamma band
spectral entropy for the detection of alcoholics. First, the
gamma sub band signals (30-50Hz) are extracted using an
elliptic band pass filter of sixth order to extract the visually
evoked potentials (VEP) signals. Prior to filtering, thresholds
of 100μv are applied to the electroencephalogram (EEG)
recordings in order to remove eye blink artefact. The power
spectral densities (PSD’s) of the gamma band are calculated
using Periodogram and the gamma band spectral entropies are
determined. These spectral entropy coefficients in the gamma
band are used as features to classify the control subjects from
their alcoholic counterparts using multilayer perceptron-back
propagation (MLP-BP) and probabilistic neural network(PNN)
classifiers. From the experimental study, it can be concluded
that the PNN classifier performs better with a classification
accuracy of ~99% (for a spread factor of < 1) than MLP
classifier. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
dc.relation.ispartofseries | Proceedings of the International Conference on Biomedical Engineering (ICoBE 2012) | en_US |
dc.subject | Alcoholics | en_US |
dc.subject | Classifier | en_US |
dc.subject | Electroencephalogram (EEG) | en_US |
dc.subject | Gamma band | en_US |
dc.subject | Neural network | en_US |
dc.subject | Spectral entropy | en_US |
dc.subject | Visually evoked potentials (VEP) | en_US |
dc.title | EEG based detection of alcoholics using spectral entropy with neural network classifiers | en_US |
dc.type | Working Paper | en_US |
dc.contributor.url | padma.shri@manipal.edu | en_US |