Longitudinal Changes in Pitch-Related Acoustic Characteristics of the Voice Throughout the Menstrual Cycle: Observational Study

Abstract BackgroundIdentifying subtle changes in the menstrual cycle is crucial for effective fertility tracking and understanding reproductive health. ObjectiveThe aim of the study is to explore how fundamental frequency features vary between menstrual phases usin...

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Bibliographic Details
Main Authors: Jaycee Kaufman, Jouhyun Jeon, Jessica Oreskovic, Anirudh Thommandram, Yan Fossat
Format: Article
Language:English
Published: JMIR Publications 2025-01-01
Series:JMIR Formative Research
Online Access:https://formative.jmir.org/2025/1/e65448
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Summary:Abstract BackgroundIdentifying subtle changes in the menstrual cycle is crucial for effective fertility tracking and understanding reproductive health. ObjectiveThe aim of the study is to explore how fundamental frequency features vary between menstrual phases using daily voice recordings. MethodsThis study analyzed smartphone-collected voice recordings from 16 naturally cycling female participants, collected every day for 1 full menstrual cycle. Fundamental frequency features (mean, SD, 5th percentile, and 95th percentile) were extracted from each voice recording. Ovulation was estimated using luteinizing hormone urine tests taken every morning. The analysis included comparisons of these features between the follicular and luteal phases and the application of changepoint detection algorithms to assess changes and pinpoint the day in which the shifts in vocal pitch occur. ResultsThe fundamental frequency SD was 9.0% (SD 2.9%) lower in the luteal phase compared to the follicular phase (95% CI 3.4%‐14.7%; PPPPPPP ConclusionsThese findings indicate that subtle variations in vocal pitch may reflect changes associated with the menstrual cycle, suggesting the potential for developing a noninvasive and convenient method for monitoring reproductive health. Changepoint detection may provide a promising avenue for future work in longitudinal fertility analysis.
ISSN:2561-326X