Latest AI and machine learning research in seizures for healthcare professionals.
Recent technological advances in machine learning offer the possibility of decoding complex datasets...
Event-related potentials (ERPs) show promise to be objective indicators of cognitive functioning. Th...
OBJECTIVE: This work proposes a machine-learning based system for a scalp EEG that flags an alarm in...
Classification of electroencephalogram (EEG) signal is important in mental decoding for brain-comput...
Real-time detection of seizure activity in epilepsy patients is critical in averting seizure activit...
The brain activity observed on EEG electrodes is influenced by volume conduction and functional conn...
OBJECTIVE: This paper investigates the hypothesis that focal seizures can be predicted using scalp e...
Epilepsy is a well-known nervous system disorder characterized by seizures. Electroencephalograms (E...
Epileptic seizures occur due to disorder in brain functionality which can affect patient's health. P...
In this work, we have used a time-frequency domain analysis method called discrete wavelet transform...
Reinforcement learning (RL) enables robots to learn its optimal behavioral strategy in dynamic envir...
BACKGROUND: Seizure prediction can increase independence and allow preventative treatment for patien...
Bullying is an everlasting phenomenon and the first, yet difficult, step towards the solution is its...
BACKGROUND: The abnormal alcohol consumption could cause toxicity and could alter the human brain's ...
When encoding visual targets using various lagged versions of a pseudorandom binary sequence of lumi...
From allowing basic communication to move through an environment, several attempts are being made in...
OBJECTIVE: Focal cortical dysplasias (FCDs) often cause pharmacoresistant epilepsy, and surgical res...
BACKGROUND: Classification of electroencephalography (EEG) signals for motor imagery based brain com...
Mental stress has been identified as one of the major contributing factors that leads to various dis...
In this paper, we propose a set of wavelet-based combined feature vectors and a Gaussian mixture mod...
OBJECTIVE: To diagnose and lateralise temporal lobe epilepsy (TLE) by building a classification syst...