Investigation of the nonlinearity in the heart rate dynamics

Effect of repetitive end-inspiration breath holding on very short-term heart rate variability in healthy humans

Very short-term heart rate variability (HRV) is thought to reflect dynamic changes in autonomic nervous activity, which is helpful in understanding the role of autonomic nervous function (ANF) in the mechanisms underlying apnea-induced cardiac arrhythmias. The goal of this study was to investigate the effect of repetitive end-inspiration breath holding on very short-term HRV. A total of 32 young healthy participants took part in the experiments. Three trials were performed, each involving seven repetitive end-inspiration breath holding and a 30 s recovery period between breath holding. Durations of breath holding in the three trials were 1:2:3. The study first evaluated the effect of analyzed data lengths on the stability of HRV indices and determined three HRV indices suitable for very short-term analysis. The results showed that in most cases, during breath holding, the square root of the mean squared differences of successive normal RR intervals (rMSSD) was significantly lower, but normalized units of the power in the low frequency band ranging from 0.04 to 0.15 Hz (nLF) and LF/high frequency (HF) were significantly higher than those during corresponding durations under the normal breathing conditions. On the contrary, during recovery after breath holding, rMSSD was significantly higher but nLF and LF/HF were lower than normal. Moreover, the durations of breath holding had no significant influence on the variations of LF/HF. In addition, as participants repeated the breath holding, HRV indices varied non-linearly. HRV changes may indicate sympathetic activation during breath holding and parasympathetic activation during recovery after breath holding. In conjunction with the existing physiological interpretation based on changes in heart rate, the results may imply that breath holding leads to both cardiac sympathetic and parasympathetic activation simultaneously, which may be a possible pathogenic factor of apnea-induced arrhythmias.

Heart-rate control during pain and suggestions of analgesia without deliberate induction of hypnosis

Heart rate and heart-rate variability (HRV) were studied through a set of different methods in high (highs) and low hypnotizable subjects (lows) not receiving any deliberate hypnotic induction in basal conditions (simple relaxation) and during nociceptive-pressor stimulation with and without suggestions of analgesia. ANOVA did not reveal any difference between highs and lows for heart rate and for the HRV indexes extracted from the series of the interbeat intervals (RR) of the ECG in the frequency (spectral analysis) and time domain (standard deviation, Poincare plot) in both basal and stimulation conditions. Factors possibly accounting for the results and likely responsible for an underestimation of group differences are discussed.

Sensitivity Analysis Applied to Artificial Neural Networks for Forecasting Time Series

This paper presents a novel procedure known as sensitivity analysis applied to a multilayer perceptron (MLP), which allows the most relevant lagged terms in time series forecasting to be identified. Second, this paper conducts a comparison of forecasting accuracy between the neural network model resulting from applying the sensitivity analysis to the network model derived from the traditional procedure and the classic ARIMA model – using the time series corresponding to the number of passengers in transit through the Balearic Islands. Our findings demonstrate that a neural network derived from sensitivity analysis provides the greatest forecasting accuracy.