Electroencephalography (EEG) is almost contaminated with many artifacts while recording
the brain signal activity. Clinical diagnostic and brain computer interface applications …

Epilepsy is a neurological disease which is difficult to diagnose accurately. An authentic
detection of focal epilepsy will help the clinicians to provide proper treatment for the patients …

Brain electrical activity recordings by electroencephalography (EEG) are often contaminated
with signal artifacts. Procedures for automated removal of EEG artifacts are frequently …

Electroencephalogram (EEG) signals may get easily contaminated by muscle artifacts,
which may lead to wrong interpretation in the brain–computer interface (BCI) system as well …

Epilepsy is a neural disorder that is associated with the central nervous system (CNS) in
which the brain activity sometimes becomes abnormal, which may lead to seizures, loss of …

This paper describes a discrete wavelet transform-based feature extraction scheme for the
classification of EEG signals. In this scheme, the discrete wavelet transform is applied on …

The electroencephalogram (EEG) signals are a big data which are frequently corrupted by
motion artifacts. As human neural diseases, diagnosis and analysis need a robust …

The determination of epileptogenic area is a prime task in presurgical evaluation. The
seizure activity can be prevented by operating the affected areas by clinical surgery. In this …

This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS)
model for classification of electroencephalogram (EEG) signals. Decision making was …

Electroencephalographic (EEG) recordings are often contaminated by artifacts, ie, signals
with noncerebral origin that might mimic some cognitive or pathologic activity, this way …