To assure aviation safety: the pilot fatigue detection based on short-term multimodal physiological signals [PDF]
Frontiers in Human NeurosciencePilot fatigue detection based on physiological signals is practical for aviation safety. Current methods face challenges in balancing the high computational cost of deep learning models with robust accuracy, especially when integrating short-term ...
Kai Chen +5 more
doaj +2 more sources
A regression method for EEG-based cross-dataset fatigue detection [PDF]
Frontiers in Physiology, 2023 Introduction: Fatigue is dangerous for certain jobs requiring continuous concentration. When faced with new datasets, the existing fatigue detection model needs a large amount of electroencephalogram (EEG) data for training, which is resource-consuming ...
Duanyang Yuan +5 more
doaj +2 more sources
Remote Tower Air Traffic Controller Multimodal Fatigue Detection [PDF]
SensorsRemote tower (rTWR) operations are reshaping air traffic control but introduce significant human-factor risks, notably cognitive fatigue induced by prolonged screen-based visual surveillance.
Weijun Pan +4 more
doaj +2 more sources
A multimodal spatio-temporal graph neural network framework for fatigue detection in tennis serving [PDF]
Frontiers in Bioengineering and BiotechnologyBackgroundThe tennis serve is a complex, high-velocity motion dependent on the efficient transfer of energy through the kinetic chain, from the lower extremities to the racquet.
Ye Yuan, Lu Wang, Hui Jia, Junfeng Jiao
doaj +2 more sources
Fatigue Detection with Spatial-Temporal Fusion Method on Covariance Manifolds of Electroencephalography [PDF]
Entropy, 2021 With the increasing pressure of current life, fatigue caused by high-pressure work has deeply affected people and even threatened their lives. In particular, fatigue driving has become a leading cause of traffic accidents and deaths.
Nan Zhao +6 more
doaj +2 more sources
Information, 2023 More than 1.3 million people are killed in traffic accidents annually. Road traffic accidents are mostly caused by human error. Therefore, an accurate driving fatigue detection system is required for drivers.
Junartho Halomoan +4 more
doaj +3 more sources
Miner Fatigue Detection from Electroencephalogram-Based Relative Power Spectral Topography Using Convolutional Neural Network [PDF]
Sensors, 2023 Fatigue of miners is caused by intensive workloads, long working hours, and shift-work schedules. It is one of the major factors increasing the risk of safety problems and work mistakes.
Lili Xu, Jizu Li, Ding Feng
doaj +2 more sources
The evaluation of cEEGrids for fatigue detection in aviation. [PDF]
Sleep AdvAbstract Operator fatigue poses a major concern in safety-critical industries such as aviation, potentially increasing the chances of errors and accidents. To better understand this risk, there is a need for noninvasive objective measures of fatigue. This study aimed to evaluate the performance of cEEGrids, a type of ear-EEG, for fatigue
van Klaren C +3 more
europepmc +3 more sources
Few-Shot Optimization for Sensor Data Using Large Language Models: A Case Study on Fatigue Detection [PDF]
SensorsIn this paper, we propose a novel few-shot optimization with Hybrid Euclidean Distance with Large Language Models (HED-LM) to improve example selection for sensor-based classification tasks.
Elsen Ronando, Sozo Inoue
doaj +2 more sources
Examining the Landscape of Cognitive Fatigue Detection: A Comprehensive Survey
TechnologiesCognitive fatigue, a state of reduced mental capacity arising from prolonged cognitive activity, poses significant challenges in various domains, from road safety to workplace productivity. Accurately detecting and mitigating cognitive fatigue is crucial
Enamul Karim +8 more
doaj +3 more sources