BACKGROUND: The powers of the low-frequency (LF) and high-frequency (HF) oscillations characterizing heart rate variability (HRV) appear to reflect, in their reciprocal relationship, changes in the state of the sympathovagal balance occurring during numerous physiological and pathophysiological conditions. However, no adequate information is available on the quantitative resolution of this methodology. METHODS AND RESULTS: We studied 22 healthy volunteers (median age, 46.5 years) who were subjected after a rest period to a series of passive head-up tilt steps randomly chosen from the following angles: 15 degrees, 30 degrees, 45 degrees, 60 degrees, and 90 degrees. From the continuous ECG, after appropriate analog-to-digital conversion, a personal computer was used to compute, with an autoregressive methodology, time and frequency domain indexes of RR interval variability. Spectral and cross-spectral analysis with the simultaneously recorded respiratory signal excluded its contribution to LF. Age was significantly correlated to variance and to the absolute values in milliseconds squared of very-low-frequency (VLF), LF, and HF components. The tilt angle was correlated to both LF and HF (expressed in normalized units [nu]) and to the LF-to-HF ratio (r = .78, -.72, and .68; respectively). Lower levels of correlation were found with HF (in ms2) and RR interval. No correlation was present between tilt angle and variance, VLF, or LF (in ms2). Individual analysis confirmed that the use of nu provided the greatest consistency of results. CONCLUSIONS: Spectral analysis of HRV, using nu or LF-to-HF ratio, appears to be capable of providing a noninvasive quantitative evaluation of graded changes in the state of the sympathovagal balance.
BACKGROUND: The powers of the low-frequency (LF) and high-frequency (HF) oscillations characterizing heart rate variability (HRV) appear to reflect, in their reciprocal relationship, changes in the state of the sympathovagal balance occurring during numerous physiological and pathophysiological conditions. However, no adequate information is available on the quantitative resolution of this methodology. METHODS AND RESULTS: We studied 22 healthy volunteers (median age, 46.5 years) who were subjected after a rest period to a series of passive head-up tilt steps randomly chosen from the following angles: 15 degrees, 30 degrees, 45 degrees, 60 degrees, and 90 degrees. From the continuous ECG, after appropriate analog-to-digital conversion, a personal computer was used to compute, with an autoregressive methodology, time and frequency domain indexes of RR interval variability. Spectral and cross-spectral analysis with the simultaneously recorded respiratory signal excluded its contribution to LF. Age was significantly correlated to variance and to the absolute values in milliseconds squared of very-low-frequency (VLF), LF, and HF components. The tilt angle was correlated to both LF and HF (expressed in normalized units [nu]) and to the LF-to-HF ratio (r = .78, -.72, and .68; respectively). Lower levels of correlation were found with HF (in ms2) and RR interval. No correlation was present between tilt angle and variance, VLF, or LF (in ms2). Individual analysis confirmed that the use of nu provided the greatest consistency of results. CONCLUSIONS: Spectral analysis of HRV, using nu or LF-to-HF ratio, appears to be capable of providing a noninvasive quantitative evaluation of graded changes in the state of the sympathovagal balance.
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