ArticleFrontiers in network physiology2023
Analyzing physiological signals recorded with a wearable sensor across the menstrual cycle using circular statistics.
Article in Frontiers in network physiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Continuous Emotion Recognition Using EDA-Graphs: A Graph Signal Processing Approach for Affective Dimension Estimation.Applied sciences (Basel, Switzerland) · 2026Article
- Women with premenstrual syndrome exhibit high interoceptive accuracy, but low awareness, with parasympathetic rebound responses from stress.Frontiers in neuroscience · 2025Article
- Electrodermal lability and sensorimotor preparation: effects on reaction time, contingent negative variation, and heart rate.Cognitive, affective & behavioral neuroscience · 2024Article
- Physiological network approach to prognosis in cirrhosis: A shifting paradigm.Physiological reports · 2024Review
- Human Activity Recognition Algorithm with Physiological and Inertial Signals Fusion: Photoplethysmography, Electrodermal Activity, and Accelerometry.Sensors (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study aims to identify the most significant features in physiological signals representing a biphasic pattern in the menstrual cycle using circular statistics which is an appropriate analytic method for the interpretation of data with a periodic nature. The results can be used empirically to determine menstrual phases. A non-uniform pattern was observed in ovulating subjects, with a significant periodicity (p
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Registered trials
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