TY - GEN
T1 - Artificial neural network for the analysis of electroencephalogram
AU - Prabhakar Nayak, K.
AU - Padmashree, T. K.
AU - Rao, S. N.
AU - Cholayya, Niranjan U.
PY - 2006/12/1
Y1 - 2006/12/1
N2 - Electroencephalography is an important tool for diagnosing, monitoring and managing neurological disorders related to epilepsy. The presence of epileptiform activity in the electroencephalogram (EEG) confirms the diagnosis of epilepsy. During the seizures, the scalp of patients with epilepsy is characterized by high amplitude synchronized periodic EEG waveforms, reflecting abnormal discharge of a large group of neurons. Between the seizures, the electroencephalogram (EEG) of the patients who suffer from epilepsy is normally characterized by occasional spikes or spike and wave complexes (inter-ictal activity). It is difficult to detect these and sometimes is missed by the clinicians who observe the paper records. The purpose of the work describes the automated detection of epileptic events based on wavelet analysis of electroencephalogram. Three layered feedforward back-propagation artificial neural network (ANN) is designed to classify the epileptic seizure and non-epileptic seizure.
AB - Electroencephalography is an important tool for diagnosing, monitoring and managing neurological disorders related to epilepsy. The presence of epileptiform activity in the electroencephalogram (EEG) confirms the diagnosis of epilepsy. During the seizures, the scalp of patients with epilepsy is characterized by high amplitude synchronized periodic EEG waveforms, reflecting abnormal discharge of a large group of neurons. Between the seizures, the electroencephalogram (EEG) of the patients who suffer from epilepsy is normally characterized by occasional spikes or spike and wave complexes (inter-ictal activity). It is difficult to detect these and sometimes is missed by the clinicians who observe the paper records. The purpose of the work describes the automated detection of epileptic events based on wavelet analysis of electroencephalogram. Three layered feedforward back-propagation artificial neural network (ANN) is designed to classify the epileptic seizure and non-epileptic seizure.
UR - https://www.scopus.com/pages/publications/47749102129
UR - https://www.scopus.com/inward/citedby.url?scp=47749102129&partnerID=8YFLogxK
U2 - 10.1109/ICISIP.2006.4286089
DO - 10.1109/ICISIP.2006.4286089
M3 - Conference contribution
AN - SCOPUS:47749102129
SN - 1424406110
SN - 9781424406111
T3 - Proceedings - 4th International Conference on Intelligent Sensing and Information Processing, ICISIP 2006
SP - 170
EP - 713
BT - Proceedings - 4th International Conference on Intelligent Sensing and Information Processing, ICISIP 2006
T2 - 4th International Conference on Intelligent Sensing and Information Processing, ICISIP 2006
Y2 - 15 December 2006 through 18 December 2006
ER -