AIMC Topic: Mental Fatigue

Clear Filters Showing 1 to 10 of 12 articles

A Deep Learning Approach for Mental Fatigue State Assessment.

Sensors (Basel, Switzerland) Jan 19, 2025
This study investigates mental fatigue in sports activities by leveraging deep learning techniques, deviating from the conventional use of heart rate variability (HRV) feature analysis found in previous research. The study utilizes a hybrid deep neur...
Humans Neural Networks, Computer Algorithms Signal Processing, Computer-Assisted Heart Rate Mental Fatigue Deep Learning Electrocardiography Support Vector Machine
View on PubMed DOI

Generalisable machine learning models trained on heart rate variability data to predict mental fatigue.

Scientific reports Nov 21, 2022
A prolonged period of cognitive performance often leads to mental fatigue, a psychobiological state that increases the risk of injury and accidents. Previous studies have trained machine learning algorithms on Heart Rate Variability (HRV) data to det...
Algorithms Heart Rate Rest Humans Machine Learning Mental Fatigue
View on PubMed DOI

Memristor-Based Neural Network Circuit of Emotion Congruent Memory With Mental Fatigue and Emotion Inhibition.

IEEE transactions on biomedical circuits and systems Aug 12, 2021
Most memristor-based neural networks only consider a single mode of memory or emotion, but ignore the relationship between emotion and memory. In this paper, a memristor-based neural network circuit of emotion congruent memory is proposed and verifie...
Computer Simulation Learning Emotions Humans Neural Networks, Computer Mental Fatigue
View on PubMed DOI

Nonintrusive Monitoring of Mental Fatigue Status Using Epidermal Electronic Systems and Machine-Learning Algorithms.

ACS sensors Jan 23, 2020
Mental fatigue, characterized by subjective feelings of "tiredness" and "lack of energy", can degrade individual performance in a variety of situations, for example, in motor vehicle driving or while performing surgery. Thus, a method for nonintrusiv...
Mental Fatigue Monitoring, Physiologic Electronics Humans Machine Learning Algorithms
View on PubMed DOI

Adaptive feature extraction in EEG-based motor imagery BCI: tracking mental fatigue.

Journal of neural engineering Jan 6, 2020
OBJECTIVE: Electroencephalogram (EEG) signals are non-stationary. This could be due to internal fluctuation of brain states such as fatigue, frustration, etc. This necessitates the development of adaptive brain-computer interfaces (BCI) whose perform...
Electroencephalography Brain-Computer Interfaces Movement Photic Stimulation Humans Mental Fatigue Unsupervised Machine Learning Imagination
View on PubMed DOI

Evaluating a Semiautonomous Brain-Computer Interface Based on Conformal Geometric Algebra and Artificial Vision.

Computational intelligence and neuroscience Nov 27, 2019
In this paper, we evaluate a semiautonomous brain-computer interface (BCI) for manipulation tasks. In such a system, the user controls a robotic arm through motor imagery commands. In traditional process-control BCI systems, the user has to provide t...
Brain Mental Fatigue Female Imagination Young Adult Robotics Humans Electroencephalography Artificial Intelligence Biomechanical Phenomena Proof of Concept Study Signal Processing, Computer-Assisted Goals Male Event-Related Potentials, P300 Models, Theoretical Brain-Computer Interfaces Motor Activity
View on PubMed DOI

Spectral and Temporal Feature Learning With Two-Stream Neural Networks for Mental Workload Assessment.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Apr 26, 2019
People's mental workload profoundly affects their work efficiency and health. Mental workload assessment can be used to effectively avoid serious accidents caused by excessive mental workload. Both electroencephalogram (EEG) spectral features and its...
Humans Workload Neural Networks, Computer Mental Fatigue Machine Learning Male Mental Processes Algorithms Brain Mapping Reproducibility of Results Electroencephalography Young Adult Adult
View on PubMed DOI

An exploratory analysis of longitudinal artificial intelligence for cognitive fatigue detection using neurophysiological based biosignal data.

Scientific reports May 6, 2025
Cognitive fatigue is a psychological condition characterized by opinions of fatigue and weakened cognitive functioning owing to constant stress. Cognitive fatigue is a critical condition that can significantly impair attention and performance, among ...
Male Algorithms Fatigue Female Adult Humans Cognition Mental Fatigue Electroencephalography Electrooculography Artificial Intelligence
View on PubMed DOI

[Mental fatigue state recognition method based on convolution neural network and long short-term memory].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Feb 25, 2024
The pace of modern life is accelerating, the pressure of life is gradually increasing, and the long-term accumulation of mental fatigue poses a threat to health. By analyzing physiological signals and parameters, this paper proposes a method that can...
Algorithms Humans Electrocardiography Neural Networks, Computer Mental Fatigue
View on PubMed DOI

Mental fatigue recognition study based on 1D convolutional neural network and short-term ECG signals.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2024
BACKGROUND: Mental fatigue has become a non-negligible health problem in modern life, as well as one of the important causes of social transportation, production and life accidents.
Adult Male Electrocardiography Neural Networks, Computer Mental Fatigue Humans Machine Learning Female
View on PubMed DOI
Popular Topics
Recent Journals