Driven by its proven therapeutic efficacy in treating movement disorders and psychiatric
conditions, neurostimulation has emerged as a promising intervention for intractable …

The nursing monitoring of electroencephalography (EEG) during neurosurgery includes
verifying the proper placement of electrodes on the patient's scalp and ensuring the accurate …

Epilepsy is a neurological disorder that is characterized by transient and unexpected
electrical disturbance of the brain. Seizure detection by electroencephalogram (EEG) is …

Electroencephalographic (EEG) signals play an important role in the detection of seizures in
epilepsy, and accurate detection of seizures can buy patients valuable treatment time …

In the research of motor imagery brain‐computer interface (MI‐BCI), traditional
electroencephalogram (EEG) signal recognition algorithms appear to be inefficient in …

The paper demonstrates various machine learning classifiers, they have been used for
detecting epileptic seizures quickly and accurately through electroencephalography (EEG) …

Epilepsy is a serious brain illness characterized by abnormal brain activity. To build a better
computer-aided diagnosis (CAD) solution, we provide a comprehensive comparison of four …

This paper deals with the detection of mu-suppression from electroencephalographic (EEG)
signals in brain-computer interface (BCI). For this purpose, an efficient algorithm is proposed …

Epilepsy is a severe neurological disorder that is usually diagnosed by using an
electroencephalogram (EEG). However, EEG signals are complex, nonlinear, and dynamic …

Driver fatigue is a major cause of traffic accidents and the electroencephalogram (EEG) is
considered one of the most reliable predictors of fatigue. This paper proposes a novel …