Enhancing Mental Fatigue Detection through Physiological Signals and Machine Learning Using Contextual Insights and Efficient Modelling

CA Cos, A Lambert, A Soni, H Jeridi, C Thieulin… - Journal of Sensor and …, 2023 - mdpi.com
This research presents a machine learning modeling process for detecting mental fatigue
using three physiological signals: electrodermal activity, electrocardiogram, and respiration …

Mental fatigue mediates the relationship between qi deficiency and academic performance among fifth-grade students aged 10–13 years

X Wang, X He, K Fu - Frontiers in Psychology, 2024 - frontiersin.org
Background Health has effects on children's academic performance. Qi deficiency is
generally used to assess an individual's health in the Chinese traditional medicine theory …

[PDF][PDF] APPLICATION OF TOPOLOGICAL MODELLING METHODS FOR DETERMINING HUMAN FATIGUE

M Erins, Z Markovics - tf.lbtu.lv
Fatigue is a complex concept that is simultaneously a physiological, psychological, and
social phenomenon which pathophysiology is still not fully understood. Solutions offered by …

Fine-Grained Noisy Segment Learning for Fatigue Detection

R Hu, L Liao, J Hu - papers.ssrn.com
In fatigue detection, fine-grained labels (seconds-based) commonly inherit coarse-grained
labels (minutes-based or more). However, due to the dynamic and time-varying nature of …