ECG and EEG based machine learning models for the classification of mental workload and stress levels for women in different menstrual phases, men, and mixed sexes

•Sex and menstrual phase differences impact stress classification performance.•ECG and EEG ML models show women in the follicular phase are the least stressed.•Higher estrogen levels in the follicular phase reduce stress vs. the luteal phase.•Combining classifiers improve stress classification over...

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Bibliographic Details
Published inBiomedical signal processing and control Vol. 95; p. 106379
Main Authors Hemakom, Apit, Atiwiwat, Danita, Israsena, Pasin
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.09.2024
Subjects
Electrocardiogram
Electroencephalogram
Machine Learning
Menstruation
Sex
Stress
Menstruation
Electroencephalogram
Machine Learning
Electrocardiogram
Stress
Sex
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Summary:•Sex and menstrual phase differences impact stress classification performance.•ECG and EEG ML models show women in the follicular phase are the least stressed.•Higher estrogen levels in the follicular phase reduce stress vs. the luteal phase.•Combining classifiers improve stress classification over individual methods.
ISSN:1746-8094
1746-8108
DOI:10.1016/j.bspc.2024.106379