Voice as a sensitive biomarker for predicting exercise intensity: a modelling study
These findings suggest that speech analysis can provide a non-invasive, real-time method for monitoring exercise intensity. The study's implications extend to personalized exercise prescriptions, chronic disease management, and the integration of speech analysis into routine health assessments. This approach promotes better exercise adherence and overall health outcomes, highlighting the potential for innovative health monitoring techniques.
Authors
- R. Q. Ma
- Shiming Zhou (ORCID: https://orcid.org/0000-0002-1597-6060)
- Dingyi Cai
- Zikang Jiang (ORCID: https://orcid.org/0000-0001-5981-2415)
- Wenfeng Hu (ORCID: https://orcid.org/0000-0002-2571-3889)
- Dandan Zhang (ORCID: https://orcid.org/0000-0001-5305-9856)
- Ting Liu (ORCID: https://orcid.org/0000-0002-6580-4523)
- Rui Hu (ORCID: https://orcid.org/0009-0004-9909-0153)
- Hexiao Ding
- Siqi Zou
Institutions
- Nanchang University (CN)
- Sun Yat-sen University (CN)
- Jinan University (CN)
- First Affiliated Hospital of Jiangxi Medical College (CN)
- Third Affiliated Hospital of Sun Yat-sen University (CN)
Publication Details
- Journal
- Frontiers in Physiology
- Published
- 2025-04-28
- DOI
- https://doi.org/10.3389/fphys.2025.1483828
- Primary Topic
- Emotion and Mood Recognition
- Type
- article
- Field-Weighted Citation Impact
- 0.00