Why the study?
Critical intensity determination often requires costly tools and multiple sessions, and alternative approaches show large individual variation, creating a need for simpler estimations with improved precision.
Does combining near-infrared spectroscopy and heart rate variability derived thresholds improve the accuracy of estimating the critical intensity of exercise in recreationally trained subjects?
Does combining near-infrared spectroscopy and heart rate variability derived thresholds improve the accuracy of estimating the critical intensity of exercise in recreationally trained subjects?
Combining near-infrared spectroscopy and heart rate variability derived thresholds provides estimations of V̇O2 and HR at the respiratory compensation point with smaller variability compared to either modality alone.
Answers are grounded in this paper and cite their sources.
May simplify critical intensity estimation; leaves open need for validation before adoption.
Fleitas-Paniagua, PR, de Almeida Azevedo, R, Trpcic, M, Murias, JM, and Rogers, B. Combining near-infrared spectroscopy and heart rate variability derived thresholds to estimate the critical intensity of exercise. J Strength Cond Res 38(1): e16-e24, 2024-Critical intensity determination often requires costly tools and several testing sessions. Alternative approaches display relatively large individual variation. Therefore, simpler estimations with improved precision are needed. This study evaluated whether averaging the heart rate (HR) and oxygen uptake (V̇O 2 ) responses associated with the muscle deoxyhemoglobin concentration breakpoint ([HHb] BP ) and the heart rate variability (HRV) given by the detrended fluctuation analysis second threshold (HRVT2) during ramp incremental (RI) test improved the accuracy of identifying the HR and V̇O 2 at the respiratory compensation point (RCP). Ten female and 11 male recreationally trained subjects performed a 15 W·minute -1 RI test. Gas exchange, near-infrared spectroscopy (NIRS), and RR interval were recorded to assess the RCP, [HHb] BP , and HRVT2. Heart rate (mean ± SD : 158 ± 14, 156 ± 13, 160 ± 14 and, 158 ± 12 bpm) and V̇O 2 (3.08 ± 0.69, 2.98 ± 0.58, 3.06 ± 0.65, and 3.02 ± 0.60 L·minute -1 ) at the RCP, [HHb] BP , HRVT2, and HRVT2&[HHb] BP average (H&H Av ), respectively, were not significantly different ( p > 0.05). The linear relationship between H&H Av and RCP was higher compared with the relationship between [HHb] BP vs RCP and HRVT2 vs RCP for both HR ( r = 0.85; r = 0.73; r = 0.79, p > 0.05) and V̇O 2 ( r = 0.94; r = 0.93; r = 0.91, p > 0.05). Intraclass correlation between RCP, [HHb] BP , HRVT2, and H&H AV was 0.93 for V̇O 2 and 0.79 for HR. The [HHb] BP and the HRVT2 independently provided V̇O 2 and HR responses that strongly agreed with those at the RCP. Combining [HHb] BP and the HRVT2 resulted in estimations of the V̇O 2 and HR at the RCP that displayed smaller variability compared with each modality alone.
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Fleitas‐Paniagua et al. (2023) studied this question.
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