Brain-computer interface: Advancement and challenges
Brain-Computer Interface (BCI) is an advanced and multidisciplinary active research domain
based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the …
based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the …
Detecting and recognizing driver distraction through various data modality using machine learning: A review, recent advances, simplified framework and open …
Driver distraction is one of the main causes of fatal traffic accidents. Therefore, the ability to
detect driver inattention is essential in building a safe yet intelligent transportation system …
detect driver inattention is essential in building a safe yet intelligent transportation system …
Driver fatigue detection systems using multi-sensors, smartphone, and cloud-based computing platforms: a comparative analysis
Q Abbas, A Alsheddy - Sensors, 2020 - mdpi.com
Internet of things (IoT) cloud-based applications deliver advanced solutions for smart cities
to decrease traffic accidents caused by driver fatigue while driving on the road …
to decrease traffic accidents caused by driver fatigue while driving on the road …
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 …
A survey on federated learning for security and privacy in healthcare applications
Technological advances in smart devices and applications targeting the Internet of
Healthcare Things provide a perfect environment for using Machine Learning-based …
Healthcare Things provide a perfect environment for using Machine Learning-based …
Adaptive single-channel EEG artifact removal with applications to clinical monitoring
Electroencephalography (EEG) has become very common in clinical practice due to its
relatively low cost, ease of installation, non-invasiveness, and good temporal resolution …
relatively low cost, ease of installation, non-invasiveness, and good temporal resolution …
Role of machine learning and deep learning techniques in EEG-based BCI emotion recognition system: a review
Emotion is a subjective psychophysiological reaction coming from external stimuli which
impacts every aspect of our daily lives. Due to the continuing development of non-invasive …
impacts every aspect of our daily lives. Due to the continuing development of non-invasive …
Efficient feature selection for electroencephalogram-based authentication
Opposed to classic authentication protocols based on credentials, biometric-based
authentication has recently emerged as a promising paradigm for achieving fast and secure …
authentication has recently emerged as a promising paradigm for achieving fast and secure …
A methodological review on prediction of multi-stage hypovigilance detection systems using multimodal features
Q Abbas, A Alsheddy - IEEE Access, 2021 - ieeexplore.ieee.org
Several hypovigilance detection systems (HDx) were developed to avoid road-side
accidents due to driver fatigue. They have suffered from several limitations. Notably many of …
accidents due to driver fatigue. They have suffered from several limitations. Notably many of …
Time-varying graph mode decomposition
N ur Rehman - arXiv preprint arXiv:2301.03496, 2023 - arxiv.org
Time-varying graph signals are alternative representation of multivariate (or multichannel)
signals in which a single time-series is associated with each of the nodes or vertex of a …
signals in which a single time-series is associated with each of the nodes or vertex of a …