Estimation of physiological exercise thresholds based on dynamical correlation properties of heart rate variability
Aerobic and anaerobic thresholds of the three-zone exercise model are often used to evaluate the exercise intensity and optimize the training load. Conventionally, these thresholds are derived from the respiratory gas exchange or blood lactate concentration measurements. Here, we introduce and valid...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-12-01
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| Series: | Frontiers in Physiology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fphys.2023.1299104/full |
| _version_ | 1827576807403028480 |
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| author | Matias Kanniainen Teemu Pukkila Joonas Kuisma Matti Molkkari Kimmo Lajunen Esa Räsänen |
| author_facet | Matias Kanniainen Teemu Pukkila Joonas Kuisma Matti Molkkari Kimmo Lajunen Esa Räsänen |
| author_sort | Matias Kanniainen |
| collection | DOAJ |
| description | Aerobic and anaerobic thresholds of the three-zone exercise model are often used to evaluate the exercise intensity and optimize the training load. Conventionally, these thresholds are derived from the respiratory gas exchange or blood lactate concentration measurements. Here, we introduce and validate a computational method based on the RR interval (RRI) dynamics of the heart rate (HR) measurement, which enables a simple, yet reasonably accurate estimation of both metabolic thresholds. The method utilizes a newly developed dynamical detrended fluctuation analysis (DDFA) to assess the real-time changes in the dynamical correlations of the RR intervals during exercise. The training intensity is shown to be in direct correspondence with the time- and scale-dependent changes in the DDFA scaling exponent. These changes are further used in the definition of an individual measure to estimate the aerobic and anaerobic threshold. The results for 15 volunteers who participated in a cyclo-ergometer test are compared to the benchmark lactate thresholds, as well as to the ventilatory threshods and alternative HR-based estimates based on the maximal HR and the conventional detrended fluctuation analysis (DFA). Our method provides the best overall agreement with the lactate thresholds and provides a promising, cost-effective alternative to conventional protocols, which could be easily integrated in wearable devices. However, detailed statistical analysis reveals the particular strengths and weaknessess of each method with respect to the agreement and consistency with the thresholds—thus underlining the need for further studies with more data. |
| first_indexed | 2024-03-08T21:17:48Z |
| format | Article |
| id | doaj.art-d16f11efb3dd4a05946d8b0fbf0a0281 |
| institution | Directory Open Access Journal |
| issn | 1664-042X |
| language | English |
| last_indexed | 2024-03-08T21:17:48Z |
| publishDate | 2023-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Physiology |
| spelling | doaj.art-d16f11efb3dd4a05946d8b0fbf0a02812023-12-21T14:49:38ZengFrontiers Media S.A.Frontiers in Physiology1664-042X2023-12-011410.3389/fphys.2023.12991041299104Estimation of physiological exercise thresholds based on dynamical correlation properties of heart rate variabilityMatias Kanniainen0Teemu Pukkila1Joonas Kuisma2Matti Molkkari3Kimmo Lajunen4Esa Räsänen5Computational Physics Laboratory, Tampere University, Tampere, FinlandComputational Physics Laboratory, Tampere University, Tampere, FinlandComputational Physics Laboratory, Tampere University, Tampere, FinlandComputational Physics Laboratory, Tampere University, Tampere, FinlandKauppi Sports Coaching Ltd., Tampere, FinlandComputational Physics Laboratory, Tampere University, Tampere, FinlandAerobic and anaerobic thresholds of the three-zone exercise model are often used to evaluate the exercise intensity and optimize the training load. Conventionally, these thresholds are derived from the respiratory gas exchange or blood lactate concentration measurements. Here, we introduce and validate a computational method based on the RR interval (RRI) dynamics of the heart rate (HR) measurement, which enables a simple, yet reasonably accurate estimation of both metabolic thresholds. The method utilizes a newly developed dynamical detrended fluctuation analysis (DDFA) to assess the real-time changes in the dynamical correlations of the RR intervals during exercise. The training intensity is shown to be in direct correspondence with the time- and scale-dependent changes in the DDFA scaling exponent. These changes are further used in the definition of an individual measure to estimate the aerobic and anaerobic threshold. The results for 15 volunteers who participated in a cyclo-ergometer test are compared to the benchmark lactate thresholds, as well as to the ventilatory threshods and alternative HR-based estimates based on the maximal HR and the conventional detrended fluctuation analysis (DFA). Our method provides the best overall agreement with the lactate thresholds and provides a promising, cost-effective alternative to conventional protocols, which could be easily integrated in wearable devices. However, detailed statistical analysis reveals the particular strengths and weaknessess of each method with respect to the agreement and consistency with the thresholds—thus underlining the need for further studies with more data.https://www.frontiersin.org/articles/10.3389/fphys.2023.1299104/fullheart rate variabilitytime series analysisdetrended fluctuation analysisaerobic thresholdanaerobic thresholdwearable health technology |
| spellingShingle | Matias Kanniainen Teemu Pukkila Joonas Kuisma Matti Molkkari Kimmo Lajunen Esa Räsänen Estimation of physiological exercise thresholds based on dynamical correlation properties of heart rate variability Frontiers in Physiology heart rate variability time series analysis detrended fluctuation analysis aerobic threshold anaerobic threshold wearable health technology |
| title | Estimation of physiological exercise thresholds based on dynamical correlation properties of heart rate variability |
| title_full | Estimation of physiological exercise thresholds based on dynamical correlation properties of heart rate variability |
| title_fullStr | Estimation of physiological exercise thresholds based on dynamical correlation properties of heart rate variability |
| title_full_unstemmed | Estimation of physiological exercise thresholds based on dynamical correlation properties of heart rate variability |
| title_short | Estimation of physiological exercise thresholds based on dynamical correlation properties of heart rate variability |
| title_sort | estimation of physiological exercise thresholds based on dynamical correlation properties of heart rate variability |
| topic | heart rate variability time series analysis detrended fluctuation analysis aerobic threshold anaerobic threshold wearable health technology |
| url | https://www.frontiersin.org/articles/10.3389/fphys.2023.1299104/full |
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