{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T00:47:50Z","timestamp":1771030070662,"version":"3.50.1"},"reference-count":48,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2021,8,22]],"date-time":"2021-08-22T00:00:00Z","timestamp":1629590400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Austrian Federal Ministry for Climate Action, Environment, Energy, Mobility, Innovation and Technology, the Austrian Federal Ministry for Digital and Economic Affairs, and the federal state of Salzburg","award":["872574"],"award-info":[{"award-number":["872574"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Recent advances in wearable technologies integrating multi-modal sensors have enabled the in-field monitoring of several physiological metrics. In sport applications, wearable devices have been widely used to improve performance while minimizing the risk of injuries and illness. The objective of this project is to estimate breathing rate (BR) from respiratory sinus arrhythmia (RSA) using heart rate (HR) recorded with a chest belt during physical activities, yielding additional physiological insight without the need of an additional sensor. Thirty-one healthy adults performed a run at increasing speed until exhaustion on an instrumented treadmill. RR intervals were measured using the Polar H10 HR monitoring system attached to a chest belt. A metabolic measurement system was used as a reference to evaluate the accuracy of the BR estimation. The evaluation of the algorithms consisted of exploring two pre-processing methods (band-pass filters and relative RR intervals transformation) with different instantaneous frequency tracking algorithms (short-term Fourier transform, single frequency tracking, harmonic frequency tracking and peak detection). The two most accurate BR estimations were achieved by combining band-pass filters with short-term Fourier transform, and relative RR intervals transformation with harmonic frequency tracking, showing 5.5% and 7.6% errors, respectively. These two methods were found to provide reasonably accurate BR estimation over a wide range of breathing frequency. Future challenges consist in applying\/validating our approaches during in-field endurance running in the context of fatigue assessment.<\/jats:p>","DOI":"10.3390\/s21165651","type":"journal-article","created":{"date-parts":[[2021,8,22]],"date-time":"2021-08-22T22:59:27Z","timestamp":1629673167000},"page":"5651","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Indirect Estimation of Breathing Rate from Heart Rate Monitoring System during Running"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1618-4054","authenticated-orcid":false,"given":"Ga\u00eblle","family":"Prigent","sequence":"first","affiliation":[{"name":"Laboratory of Movement Analysis and Measurement, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne, 1015 Lausanne, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6582-5375","authenticated-orcid":false,"given":"Kamiar","family":"Aminian","sequence":"additional","affiliation":[{"name":"Laboratory of Movement Analysis and Measurement, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne, 1015 Lausanne, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2307-8930","authenticated-orcid":false,"given":"Tiago","family":"Rodrigues","sequence":"additional","affiliation":[{"name":"Laboratory of Movement Analysis and Measurement, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne, 1015 Lausanne, Switzerland"}]},{"given":"Jean-Marc","family":"Vesin","sequence":"additional","affiliation":[{"name":"Applied Signal Processing Group, Institute of Electrical Engineering of the Swiss Federal Institute of Technology, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne, 1015 Lausanne, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8081-4423","authenticated-orcid":false,"given":"Gr\u00e9goire P.","family":"Millet","sequence":"additional","affiliation":[{"name":"Institute of Sport Sciences, University of Lausanne, 1015 Lausanne, Switzerland"}]},{"given":"Mathieu","family":"Falbriard","sequence":"additional","affiliation":[{"name":"Laboratory of Movement Analysis and Measurement, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne, 1015 Lausanne, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1434-6542","authenticated-orcid":false,"given":"Fr\u00e9d\u00e9ric","family":"Meyer","sequence":"additional","affiliation":[{"name":"Institute of Sport Sciences, University of Lausanne, 1015 Lausanne, Switzerland"}]},{"given":"Anisoara","family":"Paraschiv-Ionescu","sequence":"additional","affiliation":[{"name":"Laboratory of Movement Analysis and Measurement, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne, 1015 Lausanne, Switzerland"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"71","DOI":"10.3389\/fphys.2016.00071","article-title":"Comparison of Non-Invasive Individual Monitoring of the Training and Health of Athletes with Commercially Available Wearable Technologies","volume":"7","author":"Duking","year":"2016","journal-title":"Front. 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