{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T23:00:32Z","timestamp":1784847632072,"version":"3.55.0"},"reference-count":56,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T00:00:00Z","timestamp":1755561600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Background: Respiratory rate (RR) is a key vital sign and one of the most sensitive indicators of physiological conditions, playing a crucial role in the early identification of clinical deterioration. The monitoring of RR using electrocardiography (ECG) and photoplethysmography (PPG) aims to overcome limitations of traditional methods in clinical settings. Methods: The proposed approach extracts RR from ECG and PPG signals using different morphological and temporal features from publicly available datasets (iAMwell and Capnobase). The algorithm was used to develop and test with a selection of relevant ECG (e.g., R-peak, QRS area, and QRS slope) and PPG (amplitude and frequency modulation) characteristics. Results: The results show promising performance, with the ECG-derived signal using the R-peak\u2013based method yielding the lowest error, with a mean absolute error of 0.99 breaths\/min in the iAMwell dataset and 3.07 breaths\/min in the Capnobase dataset. In comparison, the RR PPG-derived signal showed higher errors of 5.10 breaths\/min in the iAMwell dataset and 10.66 breaths\/min in the Capnobase dataset, for the FM and AM method, respectively. Bland\u2013Altman analysis revealed a small negative bias, approximately \u22120.97 breaths\/min for the iAMwell dataset (with limits of agreement from \u22122.62 to 0.95) and \u22121.16 breaths\/min for the Capnobase dataset (limits of agreement from \u22123.37 to 1.10) in the intra-subject analysis. In the inter-subject analysis, the bias was \u22120.84 breaths\/min (limits of agreement from \u22121.76 to 0.20) for iAMwell and \u22121.22 breaths\/min (limits of agreement from \u22127.91 to 5.35) for Capnobase, indicating a slight underestimation. Conversely, the PPG-derived signal tended to overestimate RR, resulting in higher variability and reduced accuracy. These findings highlight the higher reliability of ECG-derived features for RR estimation in the analyzed datasets. Conclusion: This study suggests that the proposed approach could guide the design of cost-effective, non-invasive methods for continuous respiration monitoring, offering a reliable tool for detecting conditions like stress, anxiety, and sleep disorders.<\/jats:p>","DOI":"10.3390\/s25165136","type":"journal-article","created":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T10:59:01Z","timestamp":1755601141000},"page":"5136","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Comparison of Techniques for Respiratory Rate Extraction from Electrocardiogram and Photoplethysmogram"],"prefix":"10.3390","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1346-515X","authenticated-orcid":false,"given":"Alfonso Maria","family":"Ponsiglione","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering and Information Technology, University of Naples Federico II, Via Claudio 22, 80125 Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5874-6441","authenticated-orcid":false,"given":"Michela","family":"Russo","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Information Technology, University of Naples Federico II, Via Claudio 22, 80125 Naples, Italy"},{"name":"Neurological Clinic of Hospital San Giovanni di Dio and Ruggi d\u2019Aragona, Via San Leonardo, 80132 Salerno, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maria Giovanna","family":"Petrellese","sequence":"additional","affiliation":[{"name":"Teoresi S.p.A. Group, Via Perugia 24, 10152 Torino, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Annalisa","family":"Letizia","sequence":"additional","affiliation":[{"name":"Teoresi S.p.A. Group, Via Perugia 24, 10152 Torino, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vincenza","family":"Tufano","sequence":"additional","affiliation":[{"name":"Teoresi S.p.A. Group, Via Perugia 24, 10152 Torino, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7290-6432","authenticated-orcid":false,"given":"Carlo","family":"Ricciardi","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Information Technology, University of Naples Federico II, Via Claudio 22, 80125 Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7242-701X","authenticated-orcid":false,"given":"Annarita","family":"Tedesco","sequence":"additional","affiliation":[{"name":"Department of Public Healtcare, University of Naples Federico II, Via S. Pansini, 80131 Napoli, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4384-1646","authenticated-orcid":false,"given":"Francesco","family":"Amato","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Information Technology, University of Naples Federico II, Via Claudio 22, 80125 Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1133-1115","authenticated-orcid":false,"given":"Maria","family":"Romano","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Information Technology, University of Naples Federico II, Via Claudio 22, 80125 Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,8,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/S0167-8760(97)00052-4","article-title":"Anxiety and respiratory patterns: Their relationship during mental stress and physical load","volume":"27","author":"Masaoka","year":"1997","journal-title":"Int. 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