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Recurrence quantification analysis of heart rate variability during continuous incremental exercise test in obese subjects.
Zimatore, G; Gallotta, M C; Innocenti, L; Bonavolontà, V; Ciasca, G; De Spirito, M; Guidetti, L; Baldari, C.
Afiliação
  • Zimatore G; Department of Theoretical and Applied Sciences, eCampus University, Novedrate (CO) 22060, Italy.
  • Gallotta MC; Department of Human, Movement and Health Sciences, University of Rome "Foro Italico," Rome 00135, Italy.
  • Innocenti L; Department of Human, Movement and Health Sciences, University of Rome "Foro Italico," Rome 00135, Italy.
  • Bonavolontà V; Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari "Aldo Moro," Bari 70121, Italy.
  • Ciasca G; Institute of Physics, Fondazione Policlinico Universitario A. Gemelli IRCCS, Università Cattolica del Sacro Cuore Rome 00168, Italy.
  • De Spirito M; Institute of Physics, Fondazione Policlinico Universitario A. Gemelli IRCCS, Università Cattolica del Sacro Cuore Rome 00168, Italy.
  • Guidetti L; Department of Human, Movement and Health Sciences, University of Rome "Foro Italico," Rome 00135, Italy.
  • Baldari C; Department of Theoretical and Applied Sciences, eCampus University, Novedrate (CO) 22060, Italy.
Chaos ; 30(3): 033135, 2020 Mar.
Article em En | MEDLINE | ID: mdl-32237785
ABSTRACT
The present paper concerns a new description of changing in metabolism during incremental exercises test that permit an individually tailored program of exercises for obese subjects. We analyzed heart rate variability from RR interval time series (tachogram) with an alternative approach, the recurrence quantification analysis, that allows a description of a time series in terms of its dynamic structure and is able to identify the phase transitions. A transition in cardiac signal dynamics was detected and it perfectly reflects the aerobic threshold, as identified by gas exchange during an incremental exercise test, revealing the coupling from the respiratory system toward the heart. Moreover, our analysis shows that, in the recurrence plot of RR interval, it is possible to identify a specific pattern that allows to identify phase transitions between different dynamic regimes. The perfect match of the occurrence of the phase transitions with changes observed in the VO2 consumption, the gold standard approach to estimate thresholds, strongly supports the possibility of using our analysis of RR interval to detect metabolic threshold. In conclusion, we propose a novel nonlinear data analysis method that allows for an easy and personalized detection of thresholds both from professional and even from low-cost wearable devices, without the need of expensive gas analyzers.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Consumo de Oxigênio / Teste de Esforço / Frequência Cardíaca / Obesidade Limite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: Chaos Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Consumo de Oxigênio / Teste de Esforço / Frequência Cardíaca / Obesidade Limite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: Chaos Ano de publicação: 2020 Tipo de documento: Article