Recurrence Quantification Analysis Based Methodology in Automatic Aerobic Threshold Detection: Applicability and Accuracy across Age Groups, Exercise Protocols and Health Conditions

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Název: Recurrence Quantification Analysis Based Methodology in Automatic Aerobic Threshold Detection: Applicability and Accuracy across Age Groups, Exercise Protocols and Health Conditions
Autoři: Serantoni C., De Spirito M., Maulucci G.
Přispěvatelé: Zimatore, G., Serantoni, Cassandra, Gallotta, M. C., Meucci, M., Mourot, L., Ferrari, D., Baldari, C., De Spirito, Marco, Maulucci, Giuseppe, Guidetti, L.
Informace o vydavateli: Multidisciplinary Digital Publishing Institute (MDPI)
Rok vydání: 2024
Sbírka: Università Cattolica del Sacro Cuore: PubliCatt
Témata: aerobic transition, athletes, cardiac signal processing, cardiorespiratory monitoring, heart rate variability, nonlinear time series analysis, obesity, python code, wearable and portable sensors, Settore PHYS-06/A - Fisica per le scienze della vita, l'ambiente e i beni culturali
Popis: 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.
Druh dokumentu: article in journal/newspaper
Jazyk: English
Relation: info:eu-repo/semantics/altIdentifier/wos/WOS:001342706200001; volume:14; issue:20; firstpage:N/A; lastpage:N/A; issueyear:2024; journal:APPLIED SCIENCES; https://hdl.handle.net/10807/311687
DOI: 10.3390/app14209216
Dostupnost: https://hdl.handle.net/10807/311687
https://doi.org/10.3390/app14209216
Rights: info:eu-repo/semantics/openAccess ; license:Creative commons ; license uri:http://creativecommons.org/licenses/by/4.0/
Přístupové číslo: edsbas.272A9503
Databáze: BASE
Popis
Abstrakt: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.
DOI:10.3390/app14209216