A simple approach to determine loss of physiological complexity in heart rate series.

There are several ways to assess complexity, but no method has yet been developed for quantitatively calculating the 'loss of fractal complexity' under pathological or physiological states. In this paper, we aimed to quantitatively evaluate fractal complexity loss using a novel approach and new variables developed from Detrended Fluctuation Analysis (DFA) log-log graphics. Three study groups were established to evaluate the new approach: one for normal sinus rhythm (NSR), one for congestive heart failure (CHF), and white noise signal (WNS). ECG recordings of the NSR and CHF groups were obtained from PhysioNET Database and were used for analysis. For all groups Detrended Fluctuation Analysis scaling exponents (DFAα1, DFAα2) were determined. Scaling exponents were used to recreate the DFA log-log graph and lines. Then, the relative total logarithmic fluctuations for each sample were identified and new parameters were computed. To do this, we used a standard log-log plane to standardize the DFA log-log curves and calculated the differences between the standardized and expected areas. We quantified the total difference in standardized areas using parameters called dS1, dS2, and TdS. Our results showed that; compared to the NSR group, DFAα1was lower in both CHF and WNS groups. However, DFAα2was only reduced in the WNSgroup and not in the CHFgroup. Newly derived parameters: dS1, dS2, and TdS were significantly lowerin the NSR group compared to the CHF and WNS groups. The new parameters derived from the DFA log-log graphs are highly distinguishing for congestive heart failure and white noise signal. In addition, it may be concluded that a potential feature of our approach can be beneficial in classifying the severity of cardiac abnormalities.

Classical heart rate variability and nonlinear heart rate analysis in mice under Napentobarbital and ketamine/xylazine anesthesia.

BACKGROUND: Anesthetics are often used in animal experiments to achieve immobilization and relieve pain. However, many anesthetics can alter the dynamics of cardiovascular systems. We aimed to compare the effects of two frequently used anesthetics agents on heart rate variability (HRV) parameters in mice. METHODS: This observational study was performed between May and June 2014 in 21 male BALB/c mice aged 16-20 weeks. The animals were divided into three groups: pentobarbital (P), (n = 7); pentobarbital+fentanyl (P+F), (n = 7); and ketamine+xylazine (K+X), (n = 7). Surface electrocardiography (ECG) electrodes were placed in lead II configuration. The tachogram of RR intervals was obtained after R waves were detected using the Pan-Tompkins real-time QRS recognition algorithm. Frequency-domain, time-domain, and nonlinear HRV analyses were performed. RESULTS: The bradycardia effect was higher in the K+X group (p < 0.01). Time-domain indices were higher in group K+X compared to group P (p < 0.01) and group P+F (p < 0.001). Very low frequency (VLF) power was significantly lower in group K+X compared to group P and group P+F (p < 0.01). Low frequency (LF) power, low frequency/high frequency (LF/HF) ratio, and total power (TP) were higher in group K+X compared to group P (p < 0.01) and group P+F (p < 0.001). The detrended fluctuation analysis short-term parameter (DFAα1 ) was significantly higher in group K+X compared to group P+F (p < 0.05) and the long-term parameter (DFAα2 ) was lower in group K+X compared to group P (p < 0.05). Standard deviations SD1 and SD2 were higher in group K+X compared to group P (p < 0.001) and group P+F (p < 0.001), SD2/SD1 ratio was lower in group K+X compared to group P (p < 0.05) and group P+F (p < 0.05). Entropy measures did not differ between groups. DISCUSSION: HRV analyses, including nonlinear methods, indicated that a K+X combination reduces imbalance and disorder in the regulation of the autonomic nervous system (ANS) in comparison to both P and the P+F combination.