EEG based Major Depressive disorder and Bipolar disorder detection using Neural Networks: A review
Mental disorders represent critical public health challenges as they are leading contributors
to the global burden of disease and intensely influence social and financial welfare of …
to the global burden of disease and intensely influence social and financial welfare of …
Neuroimaging and deep learning for brain stroke detection-A review of recent advancements and future prospects
Background and objective In recent years, deep learning algorithms have created a massive
impact on addressing research challenges in different domains. The medical field also …
impact on addressing research challenges in different domains. The medical field also …
A dataset for emotion recognition using virtual reality and EEG (DER-VREEG): Emotional state classification using low-cost wearable VR-EEG headsets
NS Suhaimi, J Mountstephens, J Teo - Big Data and Cognitive Computing, 2022 - mdpi.com
Emotions are viewed as an important aspect of human interactions and conversations, and
allow effective and logical decision making. Emotion recognition uses low-cost wearable …
allow effective and logical decision making. Emotion recognition uses low-cost wearable …
Detection of mental stress through EEG signal in virtual reality environment
This paper investigates the use of an electroencephalogram (EEG) signal to classify a
subject's stress level while using virtual reality (VR). For this purpose, we designed an …
subject's stress level while using virtual reality (VR). For this purpose, we designed an …
EEG-based neural networks approaches for fatigue and drowsiness detection: A survey
Drowsiness is a state of fatigue or sleepiness characterized by a strong urge to sleep. It is
correlated with a progressive decline in response time, compromised processing of …
correlated with a progressive decline in response time, compromised processing of …
Physiological signals based anxiety detection using ensemble machine learning
Generalized Anxiety disorder (GAD) is a neurological disorder that is mentioned in the
Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-V), as well as its …
Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-V), as well as its …
Epileptical seizure detection: Performance analysis of gamma band in EEG signal using short-time Fourier transform
The EEG signal consist various frequency bands, which represents human activities like
emotion, attention sleep stage etc. For the detection of epileptical seizures, it is required to …
emotion, attention sleep stage etc. For the detection of epileptical seizures, it is required to …
[PDF][PDF] Monitoring of Epileptical Patients Using Cloud-Enabled Health-IoT System.
Accepted: 26 August 2019 The health Internet of Things (IoT) lays the basis for emergency
care for epileptic patients. The security of data transmission in the network calls for a robust …
care for epileptic patients. The security of data transmission in the network calls for a robust …
Fractal dimensions and machine learning for detection of Parkinson's disease in resting-state electroencephalography
Parkinson's disease (PD) is an incurable neurological disorder that degenerates the
cerebrospinal nervous system and hinders motor functions. Electroencephalography (EEG) …
cerebrospinal nervous system and hinders motor functions. Electroencephalography (EEG) …
Brain tumor diagnosis based on artificial neural network and a chaos whale optimization algorithm
S Gong, W Gao, F Abza - Computational Intelligence, 2020 - Wiley Online Library
Accurate and early detection of the brain tumor region has a great impact on the choice of
treatment, its success rate, and the follow‐up of the disease process over time. This study …
treatment, its success rate, and the follow‐up of the disease process over time. This study …