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Pulmonary Function Tests (PFTs)
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Effects of Surgical Masks on Cardiopulmonary Function in Healthy Subjects
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Voice as a sensitive biomarker for predicting exercise intensity: a modelling study.

Shuyi Zhou1, Ruisi Ma1, Wangjing Hu2

  • 1School of Physical Education, Jinan University, Guangzhou, Guangdong, China.

Frontiers in Physiology
|May 13, 2025
PubMed
Summary

Voice analysis accurately predicts exercise intensity, offering a non-invasive method for real-time monitoring. This omics marker has potential for personalized fitness and health management.

Keywords:
exercise intensityhealth assessmentnon-invasive monitoringspeech analysisvoice

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Area of Science:

  • Exercise Physiology
  • Speech Science
  • Biomedical Engineering

Background:

  • Monitoring exercise intensity is crucial for effective training and health management.
  • Traditional methods can be invasive or lack real-time feedback capabilities.
  • Exploring novel biomarkers like voice offers a promising alternative.

Purpose of the Study:

  • To investigate voice as a sensitive omics marker for predicting exercise intensity.
  • To evaluate the accuracy of speech analysis in differentiating exercise states.
  • To explore the potential of voice analysis in health and fitness applications.

Main Methods:

  • Ninety-two university students performed varied intensity exercises (CAMSA, Plank, PACER).
  • Speech data collected pre-, during, and post-exercise using professional equipment.
  • Acoustic features (GeMAPS, ComParE) analyzed with machine learning (SVM) for intensity classification.

Main Results:

  • Significant speech variations (duration, F0, pauses) correlated with exercise intensity.
  • Machine learning models achieved high accuracy in distinguishing exercise states.
  • Voice analysis demonstrated effectiveness in real-time exercise intensity prediction.

Conclusions:

  • Speech analysis offers a non-invasive, real-time method for monitoring exercise intensity.
  • Potential applications include personalized exercise prescriptions and chronic disease management.
  • Integrates innovative health monitoring for improved adherence and outcomes.