{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T20:21:57Z","timestamp":1774902117803,"version":"3.50.1"},"reference-count":35,"publisher":"IOP Publishing","issue":"10","license":[{"start":{"date-parts":[[2020,11,4]],"date-time":"2020-11-04T00:00:00Z","timestamp":1604448000000},"content-version":"vor","delay-in-days":34,"URL":"https:\/\/publishingsupport.iopscience.iop.org\/iop-standard\/v1"},{"start":{"date-parts":[[2020,11,4]],"date-time":"2020-11-04T00:00:00Z","timestamp":1604448000000},"content-version":"tdm","delay-in-days":34,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia","award":["SFRH\/BD\/138876\/2018"],"award-info":[{"award-number":["SFRH\/BD\/138876\/2018"]}]}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Physiol. Meas."],"published-print":{"date-parts":[[2020,10,1]]},"abstract":"Abstract<\/jats:title>\n \n Objective<\/jats:italic>\n : This study aimed at comparing different recovery-based methods to assess the highest exercise oxygen uptake value (\n \n \n \n <\/jats:tex-math>\n \n \n \n \n V<\/mml:mi>\n \u02d9<\/mml:mo>\n <\/mml:mover>\n <\/mml:mrow>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n O\n 2<\/jats:sub>\n peak) when swimming at low-moderate, heavy and severe intensities. Complementarily, the different recovery curve kinetics were analysed.\n Approach<\/jats:italic>\n : Eighteen competitive swimmers performed a 5 \u00d7 200 m front crawl intermittent protocol (0.05 m \u00b7 s\n \u22121<\/jats:sup>\n increments and 3 min intervals), with respiratory gas exchange being continuously measured breath-by-breath during and post-exercise using a portable gas analyser. The directly determined\n \n \n \n <\/jats:tex-math>\n \n \n \n \n V<\/mml:mi>\n \u02d9<\/mml:mo>\n <\/mml:mover>\n <\/mml:mrow>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n O\n 2<\/jats:sub>\n peak (\n \n \n \n <\/jats:tex-math>\n \n \n \n \n V<\/mml:mi>\n \u02d9<\/mml:mo>\n <\/mml:mover>\n <\/mml:mrow>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n O\n 2dir<\/jats:sub>\n ) was compared with the values obtained by linear and exponential backward extrapolations (of different intervals) and the recovery curve mathematical modelling.\n Main results<\/jats:italic>\n :\n \n \n \n <\/jats:tex-math>\n \n \n \n \n V<\/mml:mi>\n \u02d9<\/mml:mo>\n <\/mml:mover>\n <\/mml:mrow>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n O\n 2dir<\/jats:sub>\n rose with intensity increase: 41.96 \u00b1 6.22, 46.36 \u00b1 6.89 and 50.97 \u00b1 7.28 ml \u00b7 kg\n \u22121<\/jats:sup>\n min\n \u22121<\/jats:sup>\n for low-moderate, heavy and severe swims. Linear and exponential regressions applied to the first 20 s of recovery presented the\n \n \n \n <\/jats:tex-math>\n \n \n \n \n V<\/mml:mi>\n \u02d9<\/mml:mo>\n <\/mml:mover>\n <\/mml:mrow>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n O\n 2<\/jats:sub>\n peak values closest to\n \n \n \n <\/jats:tex-math>\n \n \n \n \n V<\/mml:mi>\n \u02d9<\/mml:mo>\n <\/mml:mover>\n <\/mml:mrow>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n O\n 2dir<\/jats:sub>\n at low-moderate (42.80 \u00b1 5.54 vs 42.88 \u00b1 5.58 ml kg\n \u22121<\/jats:sup>\n min\n \u22121<\/jats:sup>\n ), heavy (47.12 \u00b1 4.91 vs 47.48 \u00b1 5.09 ml kg\n \u22121<\/jats:sup>\n min\n \u22121<\/jats:sup>\n ) and severe intensity domains (51.24 \u00b1 6.89 vs 53.60 \u00b1 8.54 ml kg\n \u22121<\/jats:sup>\n \u00b7 min\n \u22121<\/jats:sup>\n , respectively;\n r<\/jats:italic>\n = 0.5\u20130.8,\n p<\/jats:italic>\n < 0.05). The mono-exponential function was the best fit at low-moderate and heavy intensities, while the bi-exponential function better characterized the severe exercise domain (with a slow component amplitude, time delay and time constant of 6.2 \u00b1 2.3 ml kg\n \u22121<\/jats:sup>\n min\n \u22121<\/jats:sup>\n , 116.6 \u00b1 24.3 and 39.9 \u00b1 15.2 s, respectively).\n Significance<\/jats:italic>\n : The backward extrapolation of the first 20 s of recovery is the best method to assess the\n \n \n \n <\/jats:tex-math>\n \n \n \n \n V<\/mml:mi>\n \u02d9<\/mml:mo>\n <\/mml:mover>\n <\/mml:mrow>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n O\n 2<\/jats:sub>\n peak for a large spectrum of swimming intensities. Complementarily, intensity increases imply different recovery curve kinetics, particularly a mono-exponential behaviour for low-moderate and heavy exertions and a bi-exponential dynamics for severe paces.\n <\/jats:p>","DOI":"10.1088\/1361-6579\/abb143","type":"journal-article","created":{"date-parts":[[2020,8,21]],"date-time":"2020-08-21T18:15:18Z","timestamp":1598033718000},"page":"105005","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":16,"title":["Post-swim oxygen consumption: assessment methodologies and kinetics analysis"],"prefix":"10.1088","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3910-1194","authenticated-orcid":false,"given":"Ana Sofia","family":"Monteiro","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8871-5614","authenticated-orcid":false,"given":"Diogo D","family":"Carvalho","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8904-002X","authenticated-orcid":false,"given":"Rui","family":"Azevedo","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4109-2939","authenticated-orcid":false,"given":"Jo\u00e3o Paulo","family":"Vilas-Boas","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0494-0000","authenticated-orcid":false,"given":"Rodrigo","family":"Zacca","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5811-0443","authenticated-orcid":false,"given":"Ricardo J","family":"Fernandes","sequence":"additional","affiliation":[]}],"member":"266","published-online":{"date-parts":[[2020,11,4]]},"reference":[{"key":"pmeaabb143bib1","first-page":"185","type":"journal-article","author":"Alves","year":"1996","journal-title":"Biomechanics and Medicine in Swimming VII"},{"key":"pmeaabb143bib2","doi-asserted-by":"publisher","first-page":"336","DOI":"10.1055\/s-0032-1321804","type":"journal-article","article-title":"Is the new AquaTrainer\u00ae snorkel valid for VO2 assessment in swimming?","volume":"34","author":"Baldari","year":"2013","journal-title":"Int. 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All rights, including for text and data mining, AI training, and similar technologies, are reserved.","name":"copyright_information","label":"Copyright Information"},{"value":"2020-03-29","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2020-08-21","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2020-11-04","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}