Electroencephalogram (EEG) artifacts such as eyeblink, eye movement, and muscle
movements widely contaminate the EEG signals. Those unwanted artifacts corrupt the …

Electroencephalogram (EEG) signals are progressively growing data widely known as
biomedical big data, which is applied in biomedical and healthcare research. The …

Epilepsy is a chronic neurological disorder of the brain that affects around 50 million people
worldwide. The early detection of epileptic seizures using electroencephalogram (EEG) …

Electroencephalography (EEG), as a non-invasive modality, enables the representation of
the underlying neuronal activities as electrical signals with high temporal resolution. In …

Electroencephalogram (EEG) is a technique for recording the asynchronous activation of
neuronal firing inside the brain with non-invasive scalp electrodes. Artifacts, such as eye …

An extension of the fast independent component analysis algorithm is proposed for the blind
separation of both ℚ-proper and ℚ-improper quaternion-valued signals. This is achieved by …

Eye movements are critical signs of the neurological disorders and they can be acquired by
EOG. The EOG signal is electrical signal generated due to eye ball movements and is …

The non-invasive nature of electroencephalogram (EEG) has made it an extensively used
method to understand the working of the human brain. Due to the high sensitivity of EEG, it is …

EEG signal analysis is difficult because there are so many unwanted impulses from non-
cerebral sources. Presently, methods for eliminating noise through selective frequency …

Denoising of electrooculography (EOG) signals is a challenging task as the noise and signal
share the same frequency band. This paper proposes a two-stage framework for denoising …