Application of artificial intelligence techniques for brain-computer interface in mental fatigue detection: a systematic review (2011-2022)
Mental fatigue is a psychophysical condition with a significant adverse effect on daily life,
compromising both physical and mental wellness. We are experiencing challenges in this …
compromising both physical and mental wellness. We are experiencing challenges in this …
Beyond supervised learning for pervasive healthcare
The integration of machine/deep learning and sensing technologies is transforming
healthcare and medical practice. However, inherent limitations in healthcare data, namely …
healthcare and medical practice. However, inherent limitations in healthcare data, namely …
Brain emotion perception inspired EEG emotion recognition with deep reinforcement learning
Inspired by the well-known Papez circuit theory and neuroscience knowledge of
reinforcement learning, a double dueling deep network (DQN) is built incorporating the …
reinforcement learning, a double dueling deep network (DQN) is built incorporating the …
Electroencephalogram based brain-computer interface: Applications, challenges, and opportunities
Abstract Brain-Computer Interfaces (BCI) is an exciting and emerging research area for
researchers and scientists. It is a suitable combination of software and hardware to operate …
researchers and scientists. It is a suitable combination of software and hardware to operate …
[HTML][HTML] Brain-computer interfaces in safety and security fields: risks and applications
F Brocal - Safety science, 2023 - Elsevier
With the recent increasing interest of researchers for Brain-Computer Interface (BCI),
emerges a challenge for safety and security fields. Thus, the general objective of this …
emerges a challenge for safety and security fields. Thus, the general objective of this …
Construction of universal approximators for multi-input single-output hierarchical fuzzy systems
C Sun, H Li - IEEE Transactions on Fuzzy Systems, 2023 - ieeexplore.ieee.org
As an important branch of fuzzy systems, a hierarchical fuzzy system (HFS) has a wide
range of applications in system science, medical science, and engineering. Using the …
range of applications in system science, medical science, and engineering. Using the …
Eeg-based tsk fuzzy graph neural network for driver drowsiness estimation
H Chen, J **e - Information Sciences, 2024 - Elsevier
With the development of brain-computer interface (BCI), electroencephalogram (EEG) is
considered to be one of the best physiological signals to detect the fatigue state of drivers …
considered to be one of the best physiological signals to detect the fatigue state of drivers …
Physiological computing for occupational health and safety in construction: Review, challenges and implications for future research
Recent advances in physiological computing have been made due to Artificial Intelligence
and Machine Learning, which have profoundly begun to influence occupational health and …
and Machine Learning, which have profoundly begun to influence occupational health and …
Location-Aware Encoding for Lesion Detection in Ga-DOTATATE Positron Emission Tomography Images
Objective: Lesion detection with positron emission tomography (PET) imaging is critical for
tumor staging, treatment planning, and advancing novel therapies to improve patient …
tumor staging, treatment planning, and advancing novel therapies to improve patient …
ARFN: An Attention-Based Recurrent Fuzzy Network for EEG Mental Workload Assessment
Assessing mental workload using electroencephalogram (EEG) signals is a significant
research avenue within the brain–computer interface (BCI) domain. However, due to the low …
research avenue within the brain–computer interface (BCI) domain. However, due to the low …