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Intraindividual validation of heart rate variability indexes to measure vagal effects on hearts

¹KIHU–Research Institute for Olympic Sports, Jyväskylä, Finland; and ²Department of Biology of Physical Activity, University of Jyväskylä, Jyväskylä, Finland

Submitted 18 January 2005 ; accepted in final form 26 August 2005

Heart rate variability (HRV) has been widely used as a measure of vagal activation in physiological, psychological, and clinical examinations. We studied the within-subject quantitative relationship between HRV and vagal effects on the heart in different body postures during a gradually decreasing vagal blockade. Electrocardiogram and respiratory frequency were measured in subjects (8 endurance athletes and 10 participants of nonendurance sports) in supine, sitting, and standing postures before the blockade, under vagal blockade (atropine sulfate, 0.04 mg/kg), and four times during a 150-min recovery from the blockade. Fast Fourier transform was used to calculate low-frequency power (LFP, 0.04–0.15 Hz), high-frequency power (HFP, 0.15–0.40 Hz), and total power (TP, 0.04–0.40 Hz). A within-subject linear regression analysis of recovery time on each HRV index was conducted. Complete vagal blockade decreased all HRV significantly, particularly HFP (P < 0.001). A linear fit explained a large portion of the within-subject variance between recovery time and natural log-transformed (ln) HRV indexes in every posture, with coefficients of determination (R²) in the supine posture [means (SD)]: 98 (SD 2)% for mean R-R interval, 87 (SD 10)% for lnLFP, 87 (SD 13)% for lnHFP, and 91 (SD 10)% for lnTP. Neither body posture nor endurance-training background had an impact on R² values. There was marked between-subject variation in the R² values, slopes, and intercepts. In conclusion, all HRV, particularly HFP, is predominantly under vagal control. Within subjects, lnLFP, lnHFP, and lnTP increased linearly with the gradually decreasing vagal blockade in all postures.

autonomic nervous system; parasympathetic; power spectral analysis