{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T12:51:30Z","timestamp":1778676690461,"version":"3.51.4"},"reference-count":37,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2023,3,31]],"date-time":"2023-03-31T00:00:00Z","timestamp":1680220800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"publisher","award":["PROJ-01003"],"award-info":[{"award-number":["PROJ-01003"]}],"id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"publisher","award":["813234"],"award-info":[{"award-number":["813234"]}],"id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"publisher","award":["813843"],"award-info":[{"award-number":["813843"]}],"id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Horizon 2020 Framework Programme","award":["PROJ-01003"],"award-info":[{"award-number":["PROJ-01003"]}]},{"name":"Horizon 2020 Framework Programme","award":["813234"],"award-info":[{"award-number":["813234"]}]},{"name":"Horizon 2020 Framework Programme","award":["813843"],"award-info":[{"award-number":["813843"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Objective: The employment of wearable systems for continuous monitoring of vital signs is increasing. However, due to substantial susceptibility of conventional bio-signals recorded by wearable systems to motion artifacts, estimation of the respiratory rate (RR) during physical activities is a challenging task. Alternatively, functional Near-Infrared Spectroscopy (fNIRS) can be used, which has been proven less vulnerable to the subject\u2019s movements. This paper proposes a fusion-based method for estimating RR during bicycling from fNIRS signals recorded by a wearable system. Methods: Firstly, five respiratory modulations are extracted, based on amplitude, frequency, and intensity of the oxygenated hemoglobin concentration (O2Hb) signal. Secondly, the dominant frequency of each modulation is computed using the fast Fourier transform. Finally, dominant frequencies of all modulations are fused, based on averaging, to estimate RR. The performance of the proposed method was validated on 22 young healthy subjects, whose respiratory and fNIRS signals were simultaneously recorded during a bicycling task, and compared against a zero delay Fourier domain band-pass filter. Results: The comparison between results obtained by the proposed method and band-pass filtering indicated the superiority of the former, with a lower mean absolute error (3.66 vs. 11.06 breaths per minute, p&lt;0.05). The proposed fusion strategy also outperformed RR estimations based on the analysis of individual modulation. Significance: This study orients towards the practical limitations of traditional bio-signals for RR estimation during physical activities.<\/jats:p>","DOI":"10.3390\/s23073632","type":"journal-article","created":{"date-parts":[[2023,3,31]],"date-time":"2023-03-31T02:08:01Z","timestamp":1680228481000},"page":"3632","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Estimation of Respiratory Rate during Biking with a Single Sensor Functional Near-Infrared Spectroscopy (fNIRS) System"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6625-7923","authenticated-orcid":false,"given":"Mohammad","family":"Shahbakhti","sequence":"first","affiliation":[{"name":"Artinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The Netherlands"},{"name":"Biomedical Engineering Institute, Kaunas University of Technology, K. Barsausko 59, LT-51423 Kaunas, Lithuania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2751-1586","authenticated-orcid":false,"given":"Naser","family":"Hakimi","sequence":"additional","affiliation":[{"name":"Artinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The Netherlands"},{"name":"Department of Neonatology, Wilhelmina Children\u2019s Hospital, University Medical Center Utrecht, Lundlaan 6, 3584 EA Utrecht, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0159-431X","authenticated-orcid":false,"given":"J\u00f6rn M.","family":"Horschig","sequence":"additional","affiliation":[{"name":"Artinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marianne","family":"Floor-Westerdijk","sequence":"additional","affiliation":[{"name":"Artinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jurgen","family":"Claassen","sequence":"additional","affiliation":[{"name":"Donders Institute for Brain, Cognition and Behaviour, Radboud University, Houtlaan 4, 6525 XZ Nijmegen, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Willy N. J. M.","family":"Colier","sequence":"additional","affiliation":[{"name":"Artinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"13462","DOI":"10.1109\/JSEN.2022.3177205","article-title":"Wearable Multimodal Vital Sign Monitoring Sensor With Fully Integrated Analog Front End","volume":"22","author":"Wang","year":"2022","journal-title":"IEEE Sens. J."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"De Fazio, R., Mastronardi, V.M., De Vittorio, M., and Visconti, P. (2023). Wearable Sensors and Smart Devices to Monitor Rehabilitation Parameters and Sports Performance: An Overview. Sensors, 23.","DOI":"10.3390\/s23041856"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Moshawrab, M., Adda, M., Bouzouane, A., Ibrahim, H., and Raad, A. (2023). 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