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© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

A new method based on the Recurrence Quantification Analysis (RQA) of the heart rate (HR) offers an objective, efficient alternative to traditional methods for Aerobic Threshold (AerT) identification that have practical limitations due to the complexity of equipment and interpretation. This study aims to validate the RQA-based method’s applicability across varied demographics, exercise protocols, and health status. Data from 123 cardiopulmonary exercise tests were analyzed, and participants were categorized into four groups: athletes, young athletes, obese individuals, and cardiac patients. Each participant’s AerT was assessed using both traditional ventilatory equivalent methods and the automatic RQA-based method. Ordinary Least Products (OLP) regression analysis revealed strong correlations (r > 0.77) between the RQA-based and traditional methods in both oxygen consumption (VO2) and HR at the AerT. Mean percentage differences in HR were below 2.5%, and the Technical Error for HR at AerT was under 8%. The study validates the RQA-based method, directly applied to HR time series, as a reliable tool for the automatic detection of the AerT, demonstrating its accuracy across diverse age groups and fitness levels. These findings suggest a versatile, cost-effective, non-invasive, and objective tool for personalized exercise prescription and health risk stratification, thereby fulfilling the study’s goal of broadening the method’s applicability.

Details

Title
Recurrence Quantification Analysis Based Methodology in Automatic Aerobic Threshold Detection: Applicability and Accuracy across Age Groups, Exercise Protocols and Health Conditions
Author
Zimatore, Giovanna 1   VIAFID ORCID Logo  ; Serantoni, Cassandra 2   VIAFID ORCID Logo  ; Gallotta, Maria Chiara 3 ; Meucci, Marco 4   VIAFID ORCID Logo  ; Mourot, Laurent 5   VIAFID ORCID Logo  ; Ferrari, Dafne 6   VIAFID ORCID Logo  ; Baldari, Carlo 7   VIAFID ORCID Logo  ; De Spirito, Marco 2   VIAFID ORCID Logo  ; Maulucci, Giuseppe 2   VIAFID ORCID Logo  ; Guidetti, Laura 8   VIAFID ORCID Logo 

 Department of Theoretical and Applied Sciences, eCampus University, 22060 Novedrate, Italy; [email protected] (G.Z.); [email protected] (C.B.); CNR Institute for Microelectronics and Microsystems (IMM), 40129 Bologna, Italy 
 Metabolic Intelligence Lab, Neuroscience, Università Cattolica del Sacro Cuore, 00168 Rome, Italy; [email protected] (C.S.); [email protected] (G.M.); Physics for Life Science, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, 00168 Rome, Italy 
 Department of Physiology and Pharmacology “Vittorio Erspamer”, Sapienza University of Rome, 00185 Rome, Italy; [email protected] 
 Department of Health and Exercise Science, Appalachian State University, Boone, NC 28608, USA; [email protected] 
 Université de Franche-Comté, SINERGIES, F-25000 Besançon, France; [email protected]; Department of Biological Sciences, Faculty of Science, Thompson Rivers University, Kamloops, BC V2C 0C8, Canada 
 Department of Human Sciences, Health and Health Care Professions, Link Campus University, 00165 Rome, Italy; [email protected] 
 Department of Theoretical and Applied Sciences, eCampus University, 22060 Novedrate, Italy; [email protected] (G.Z.); [email protected] (C.B.) 
 Department Unicusano, Niccolò Cusano University, 00166 Rome, Italy; [email protected] 
First page
9216
Publication year
2024
Publication date
2024
Publisher
MDPI AG
e-ISSN
20763417
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3120526799
Copyright
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.