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Exploring the Effects of Sleep Deprivation on Physical Performance: An EEG Study in the Context of High-Intensity Endurance.
Sports Med Open
January 2025
Department of Physical Education, Tongji University, Shanghai, 200000, China.
Background: While the effects of sleep deprivation on cognitive function are well-documented, its impact on high-intensity endurance performance and underlying neural mechanisms remains underexplored, especially in the context of search and rescue operations where both physical and mental performance are essential. This study examines the neurophysiological basis of sleep deprivation on high-intensity endurance using electroencephalography (EEG). In this crossover study, twenty firefighters were subjected to both sleep deprivation (SD) and normal sleep conditions, with each participant performing endurance treadmill exercise the following morning after each condition.
View Article and Find Full Text PDFDetermination of the Time-frequency Features for Impulse Components in EEG Signals.
Neuroinformatics
January 2025
Institute of Mathematics, University of Kassel, Heinrich-Plett-Str. 40, Kassel, 34132, Germany.
Accurately identifying the timing and frequency characteristics of impulse components in EEG signals is essential but limited by the Heisenberg uncertainty principle. Inspired by the visual system's ability to identify objects and their locations, we propose a new method that integrates a visual system model with wavelet analysis to calculate both time and frequency features of local impulses in EEG signals. We develop a mathematical model based on invariant pattern recognition by the visual system, combined with wavelet analysis using Krawtchouk functions as the mother wavelet.
View Article and Find Full Text PDFCancer is a condition in which cells in the body grow uncontrollably, often forming tumours and potentially spreading to various areas of the body. Cancer is a hazardous medical case in medical history analysis. Every year, many people die of cancer at an early stage.
View Article and Find Full Text PDFID3RSNet: cross-subject driver drowsiness detection from raw single-channel EEG with an interpretable residual shrinkage network.
Front Neurosci
January 2025
School of Data Science, Lingnan University, Hong Kong SAR, China.
Accurate monitoring of drowsy driving through electroencephalography (EEG) can effectively reduce traffic accidents. Developing a calibration-free drowsiness detection system with single-channel EEG alone is very challenging due to the non-stationarity of EEG signals, the heterogeneity among different individuals, and the relatively parsimonious compared to multi-channel EEG. Although deep learning-based approaches can effectively decode EEG signals, most deep learning models lack interpretability due to their black-box nature.
View Article and Find Full Text PDFProtocol for prognosticating PPD using EEG changes during labor pain by uterine contractions: a prospective cohort study in the first stage of labor.
BMC Pregnancy Childbirth
January 2025
Department of Anesthesiology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Background: Lack of motivation and behavioral abnormalities are the hallmarks of postpartum depression (PPD). Severe uterine contractions during labor are pain triggers for psychiatric disorders, including PPD in women during the puerperium. Creating biomarkers to monitor PPD may help in its early detection and treatment.
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