The effect of respiratory oscillations in heart rate on detrended fluctuation analysis

Characterization of heart rate using detrended fluctuation analysis (DFA) is impeded by respiratory oscillations. In particular, the short-term exponent measured from 15 to 30 beats is compromised in the DFA. We reconstruct respiratory signal from electrocardiograms and attenuate the respiratory oscillation in the heart rate using a frequency-dependent subtraction approach. We validate this method by applying it to an electrocardiogram signal simulated using a coupled differential equation with the respiratory oscillation modelled using a sine function. The exponent estimated using the proposed approach agreed with the exponent incorporated in the model within a narrow range. In contrast, the exponent obtained from the raw data deviated from the expected value. Furthermore, the exponents obtained for the raw heart rate are smaller than the exponents obtained for the respiration oscillation attenuated heart rate. We apply this approach to heart rate measured from 12 preterm infants that were being treated for prematurity related complications. As observed in the simulated data, we show that compared to the raw heart rate, the respiratory oscillation attenuated heart rate shows higher short-term exponent (p < 0.001)

Detrended fluctuation analysis of non-stationary cardiac beat-to-beat interval of sick infants

We performed detrended fluctuation analysis (DFA) of cardiac beat-to-beat intervals (RRis) collected from sick newborn infants over 1–4 day periods. We calculated four different metrics from the DFA fluctuation function: the DFA exponents $\alpha_{L}$ (>40 beats up to one-fourth of the record length), $\alpha_{s}$ (15–30 beats), root-mean-square (RMS) fluctuation on a short-time scale (20–50 beats), and RMS fluctuation on a long-time scale (110–150 beats). Except $\alpha_{L}$ , all metrics clearly distinguished two groups of newborn infants (favourable vs. adverse) with well-characterized outcomes. However, the RMS fluctuations distinguished the two groups more consistently over time compared to $\alpha_{S}$ . Furthermore, RMS distinguished the RRi of the two groups earlier compared to the DFA exponent. In all the three measures, the favourable outcome group displayed higher values, indicating a higher magnitude of (auto-)correlation and variability, thus normal physiology, compared to the adverse outcome group

Heart rate variability in encephalopathic newborns during and after therapeutic hypothermia

OBJECTIVE: To evaluate whether HRV measures are predictive of neurological outcome in babies with hypoxic ischemic encephalopathy (HIE). STUDY DESIGN: This case-control investigation included 20 term encephalopathic newborns treated with systemic hypothermia in a regional NICU. Electrocardiographic data were collected continuously during hypothermia. Spectral analysis of beat-to-beat heart rate interval was used to quantify HRV. HRV measures were compared between infants with adverse outcome (death or neurodevelopmental impairment at 15 months, n=10) and those with favorable outcome (survivors without impairment, n=10). RESULTS: HRV differentiated infants by outcome during hypothermia through post-rewarming, with the best distinction between groups at 24 hours and after 80 hours of life. CONCLUSIONS: HRV during hypothermia treatment distinguished HIE babies who subsequently died or had neurodevelopmental impairment from intact survivors. This physiological biomarker may identify infants in need of adjuvant neuroprotective interventions. These findings warrant further investigation in a larger population of infants with HIE