Cognitive workload recognition using EEG signals and machine learning: A review
Machine learning and its subfield deep learning techniques provide opportunities for the
development of operator mental state monitoring, especially for cognitive workload …
development of operator mental state monitoring, especially for cognitive workload …
Immersive media experience: a survey of existing methods and tools for human influential factors assessment
Virtual reality (VR) applications, especially those where the user is untethered to a computer,
are becoming more prevalent as new hardware is developed, computational power and …
are becoming more prevalent as new hardware is developed, computational power and …
Adaptive filtering for improved EEG-based mental workload assessment of ambulant users
Recently, due to the emergence of mobile electroencephalography (EEG) devices,
assessment of mental workload in highly ecological settings has gained popularity. In such …
assessment of mental workload in highly ecological settings has gained popularity. In such …
Pass: a multimodal database of physical activity and stress for mobile passive body/brain-computer interface research
With the burgeoning of wearable devices and passive body/brain-computer interfaces
(B/BCIs), automated stress monitoring in everyday settings has gained significant attention …
(B/BCIs), automated stress monitoring in everyday settings has gained significant attention …
Reliability of mental workload index assessed by eeg with different electrode configurations and signal pre-processing pipelines
Background and Objective: Mental workload (MWL) is a relevant construct involved in all
cognitively demanding activities, and its assessment is an important goal in many research …
cognitively demanding activities, and its assessment is an important goal in many research …
The moderation effects of task attributes and mental fatigue on post-interruption task performance in a concurrent multitasking environment
Y Chen, W Fang, B Guo, H Bao - Applied Ergonomics, 2022 - Elsevier
In a concurrent multitasking environment, performing many types of tasks increases task
complexity, and working long hours makes a person susceptible to mental fatigue. Emerging …
complexity, and working long hours makes a person susceptible to mental fatigue. Emerging …
A Connectivity-Aware Graph Neural Network for Real-Time Drowsiness Classification
Drowsy driving is one of the primary causes of driving fatalities. Electroencephalography
(EEG), a method for detecting drowsiness directly from brain activity, has been widely used …
(EEG), a method for detecting drowsiness directly from brain activity, has been widely used …
Instrumenting a virtual reality headset for at-home gamer experience monitoring and behavioural assessment
Measuring a gamer's behaviour and perceived gaming experience in real-time can be
crucial not only to assess game usability, but to also adjust the game play and content in real …
crucial not only to assess game usability, but to also adjust the game play and content in real …
Movement artifact-robust mental workload assessment during physical activity using multi-sensor fusion
Mental workload assessment is of great importance for safety critical applications, especially
in situations that involve physical demands, such as with first responders (eg, paramedics …
in situations that involve physical demands, such as with first responders (eg, paramedics …
[HTML][HTML] An Empirical Model-Based Algorithm for Removing Motion-Caused Artifacts in Motor Imagery EEG Data for Classification Using an Optimized CNN Model
Electroencephalography (EEG) is a non-invasive technique with high temporal resolution
and cost-effective, portable, and easy-to-use features. Motor imagery EEG (MI-EEG) data …
and cost-effective, portable, and easy-to-use features. Motor imagery EEG (MI-EEG) data …