Multiscale Cumulative Residual Dispersion Entropy with Applications to Cardiovascular Signals.

Heart rate variability (HRV) is used as an index reflecting the adaptability of the autonomic nervous system to external stimuli and can be used to detect various heart diseases. Since HRVs are the time series signal with nonlinear property, entropy has been an attractive analysis method. Among the various entropy methods, dispersion entropy (DE) has been preferred due to its ability to quantify the time series' underlying complexity with low computational cost. However, the order between patterns is not considered in the probability distribution of dispersion patterns for computing the DE value. Here, a multiscale cumulative residual dispersion entropy (MCRDE), which employs a cumulative residual entropy and DE estimation in multiple temporal scales, is presented. Thus, a generalized and fast estimation of complexity in temporal structures is inherited in the proposed MCRDE. To verify the performance of the proposed MCRDE, the complexity of inter-beat interval obtained from ECG signals of congestive heart failure (CHF), atrial fibrillation (AF), and the healthy group was compared. The experimental results show that MCRDE is more capable of quantifying physiological conditions than preceding multiscale entropy methods in that MCRDE achieves more statistically significant cases in terms of p-value from the Mann-Whitney test.

Cardiac arrhythmia detection using cross-sample entropy measure based on short and long RR interval series.

Background: Accurate arrhythmia (atrial fibrillation (AF) and congestive heart failure (CHF)) detection is still a challenge in the biomedical signal-processing field. Different linear and nonlinear measures of the electrocardiogram (ECG) signal analysis are used to fix this problem. Methods: Sample entropy (SampEn) is used as a nonlinear measure based on single series to detect healthy and arrhythmia subjects. To follow this measure, the proposed work presents a nonlinear technique, namely, the cross-sample entropy (CrossSampEn) based on two series to quantify healthy and arrhythmia subjects. Results: The research work consists of 10 records of normal sinus rhythm, 20 records of Fantasia (old group), 10 records of AF, and 10 records of CHF. The method of CrossSampEn has been proposed to obtain the irregularity between two same and different R-R (R peak to peak) interval series of different data lengths. Unlike the SampEn technique, the CrossSampEn technique never awards a 'not defined' value for very short data lengths and was found to be more consistent than SampEn. One-way ANOVA test has validated the proposed algorithm by providing a large F value and p < .0001. The proposed algorithm is also verified by simulated data. Conclusions: It is concluded that different RR interval series of approximate 1500 data points and same RR interval series of approximate 1000 data points are required for health-status detection with embedded dimensions, M = 2 and threshold, r = .2. Also, CrossSampEn has been found more consistent than Sample entropy algorithm.

Heart Rate Variability and Cardiorespiratory Fitness in Youth Populations: The Impact of Heart Rate on Data Analysis.

The positive association between heart rate variability and cardiorespiratory fitness in youth populations is unclear. In this regard, several methodological aspects related to heart rate variability analysis could partially explain the disagreement between studies. To the best of the authors' knowledge, the influence of the heart rate on data analysis is unclear. In the present short communication, we discuss the impact of the heart rate on the associations between heart rate variability and cardiorespiratory fitness in youth. In addition, we proposed some aspects that should be considered for statistical analyses when the relationship between heart rate variability and cardiorespiratory fitness is studied. Finally, we should acknowledge that these recommendations may be applicable for other health-related outcomes different than cardiorespiratory fitness (e.g., inflammatory markers, cognition, cardiovascular disease status).

Analysis of Poincaré plot derived from 5-min electrocardiography in dogs with myxomatous mitral valve disease.

BACKGROUND: Evaluation of heart rate variability (HRV) is used for risk assessment in a variety of cardiac diseases including myxomatous mitral valve degeneration (MMVD). OBJECTIVES: To compare the geometric analysis of HRV using visual patterns of Poincaré plot among different classes of MMVD in dogs and to analyse the differences in beat-to-beat variability using tachograms and sequential Poincaré plots among different shapes. ANIMALS AND METHODS: Healthy and MMVD dogs were retrospectively reviewed. Five-minute ECG data was used to create Poincaré plots and shapes were compared among groups. Furthermore, a sub-analysis of 50 consecutive R-R intervals was performed. Pearson Chi-square with adjusted standardized residuals was used to compare the categorical data between groups. RESULTS: Fifteen healthy dogs and 157 dogs with MMVD were included in the study. Normal and B1 groups showed a predominance of triangular shape (73% and 60% respectively; p < 0.05). In B2 group the predominant shape was comet (40%; p < 0.05) while comet and torpedo were predominant in Ca group (41% and 36% respectively; p < 0.05). Visual geometric analysis revealed a lower dispersion of the cloud clustering towards the left lower corner of the plot with MMVD progression. Diamond and triangle revealed a lower mean heart rate compared to comet and torpedo shapes (p < 0.01). Interclass correlation between 3 observers was 0.906 (95% CI of 0.8 - 0.96). CONCLUSIONS: Poincaré plot shape changes with MMVD progression suggesting that geometrical analysis of HRV in dogs with cardiac conditions could be a useful tool in the risk assessment and further studies are warranted.

Novel AI-based HRV analysis (NAIHA) in healthcare automation and related applications.

BACKGROUND: Heart rate variability (HRV) analysis computed on R-R interval series of ECG records with heavy burden of ectopic beats or non-sinus rhythm can significantly distort HRV parameters and hence clinically ineligible for HRV analysis. Yet, existing algorithmic methods of HRV analysis do not check such eligibility and require manual identification of eligible window (portion of ECG record) to ensure reliability. OBJECTIVE: We aimed to propose a robust algorithm with a sliding window feature to automate the identification of an eligible window, if available, which compute HRV parameters within that window obviating manual input. METHODS: The proposed algorithm classifies each window as either eligible or ineligible. With a window classified eligible, we stop sliding through the record, otherwise we move to the next window and repeat the eligibility identification process, until either an eligible window is found, or all windows are exhausted. RESULTS: When evaluated on random subset of 100 records from MIMIC-III waveform database, the proposed algorithm excluded every ineligible record, and missed only 1.25% of eligible ones. The HRV parameters computed using proposed method closely approximated the standard HRV analysis with Pearson correlation coefficients (ideally one) and fractions of variance unexplained (ideally zero) ranging from 96.3% to 99.8% and 0.34% to 7.43%, respectively. CONCLUSIONS: When translated into practice, proposed algorithm will reduce clinicians'' burden without compromising the accuracy of HRV analysis, potentially leading to its wider adoption.

Methods for analyzing infant heart rate variability: A preliminary study.

Heart rate (HR) and heart rate variability (HRV) reflect autonomic development in infants. To better understand the autonomic response in infants, reliable HRV recordings are vital, yet no protocol exists. The purpose of this paper is to present reliability of a common procedure for analysis from two different file types. In the procedure, continuous electrocardiograph recordings of 5-10 min are obtained at rest in infants at 1 month of age by using a Hexoskin Shirt-Junior's (Carre Technologies Inc., Montreal, QC, Canada). Electrocardiograph (ECG; .wav) and R-R interval (RRi; .csv) files are extracted. The RRi of the ECG signal is generated by VivoSense (Great Lakes NeuroTechnologies, Independence, OH). Two MATLAB (The MathWorks, Inc., Natick, MA) scripts converted files for analysis with Kubios HRV Premium (Kubios Oy, Kuopio, Finland). A comparison was made between RRi and ECG files for HR and HRV parameters, and then tested with t tests and correlations via SPSS. There are significant differences in root mean squared successive differences between recording types, with only HR and low-frequency measures significantly correlated together. Recording with Hexoskin and analysis with MATLAB and Kubios enable infant HRV analysis. Differences in outcomes exist between procedures, and standard methodology for infant HR analysis is needed.

Effects of Ballistocardiogram Peak Detection Jitters on the Quality of Heart Rate Variability Features: A Simulation-Based Case Study in the Context of Sleep Staging.

Heart rate variability (HRV) features support several clinical applications, including sleep staging, and ballistocardiograms (BCGs) can be used to unobtrusively estimate these features. Electrocardiography is the traditional clinical standard for HRV estimation, but BCGs and electrocardiograms (ECGs) yield different estimates for heartbeat intervals (HBIs), leading to differences in calculated HRV parameters. This study examines the viability of using BCG-based HRV features for sleep staging by quantifying the impact of these timing differences on the resulting parameters of interest. We introduced a range of synthetic time offsets to simulate the differences between BCG- and ECG-based heartbeat intervals, and the resulting HRV features are used to perform sleep staging. Subsequently, we draw a relationship between the mean absolute error in HBIs and the resulting sleep-staging performances. We also extend our previous work in heartbeat interval identification algorithms to demonstrate that our simulated timing jitters are close representatives of errors between heartbeat interval measurements. This work indicates that BCG-based sleep staging can produce accuracies comparable to ECG-based techniques such that at an HBI error range of up to 60 ms, the sleep-scoring error could increase from 17% to 25% based on one of the scenarios we examined.

Decoding the correlation between heart activation and walking path by information-based analysis.

BACKGROND: One of the important areas of heart research is to analyze heart rate variability during (HRV) walking. OBJECTIVE: In this research, we investigated the correction between heart activation and the variations of walking paths. METHOD: We employed Shannon entropy to analyze how the information content of walking paths affects the information content of HRV. Eight healthy students walked on three designed walking paths with different information contents while we recorded their ECG signals. We computed and analyzed the Shannon entropy of the R-R interval time series (as an indicator of HRV) versus the Shannon entropy of different walking paths and accordingly evaluated their relation. RESULTS: According to the obtained results, walking on the path that contains more information leads to less information in the R-R time series. CONCLUSION: The analysis method employed in this research can be extended to analyze the relation between other physiological signals (such as brain or muscle reactions) and the walking path.

A Novel Adaptive Noise Elimination Algorithm in Long RR Interval Sequences for Heart Rate Variability Analysis.

As heart rate variability (HRV) studies become more and more prevalent in clinical practice, one of the most common and significant causes of errors is associated with distorted RR interval (RRI) data acquisition. The nature of such artifacts can be both mechanical as well as software based. Various currently used noise elimination in RRI sequences methods use filtering algorithms that eliminate artifacts without taking into account the fact that the whole RRI sequence time cannot be shortened or lengthened. Keeping that in mind, we aimed to develop an artifacts elimination algorithm suited to long-term (hours or days) sequences that does not affect the overall structure of the RRI sequence and does not alter the duration of data registration. An original adaptive smart time series step-by-step analysis and statistical verification methods were used. The adaptive algorithm was designed to maximize the reconstruction of the heart-rate structure and is suitable for use, especially in polygraphy. The authors submit the scheme and program for use.

Validity of a Smartphone Application in Calculating Measures of Heart Rate Variability.

The purpose of the current study was to determine the concurrent validity of the Elite HRV smartphone application when calculating heart rate variability (HRV) metrics in reference to an independent software criterion. A total of 5 minutes of R−R interval and natural log of root mean square of the successive differences (lnRMSSD) resting HRV data were simultaneously collected using two Polar H10 heart rate monitors (HRMs) in both the seated and supine positions from 22 participants (14 males, 8 females). One H10 HRM was paired with a Polar V800 watch and one with the Elite HRV application. When no artifact correction was applied, significant, but small, differences in the lnRMSSD data were observed between the software in the seated position (p = 0.022), and trivial and nonstatistically significant differences were observed in the supine position (p = 0.087). However, significant differences (p > 0.05) in the lnRMSSD data were no longer identifiable in either the seated or the supine positions when applying Very Low, Low, or Automatic artifact-correction filters. Additionally, excellent agreements (ICC3,1 = 0.938 − 0.998) and very strong to near-perfect (r = 0.889 − 0.997) relationships were observed throughout all correction levels. The Elite HRV smartphone application is a valid tool for calculating resting lnRMSSD HRV metrics.

Factors Associated with Reduced Heart Rate Variability in the General Japanese Population: The Iwaki Cross-Sectional Research Study.

Although many studies have reported factors associated with reduced heart rate variability (HRV) in Western populations, evidence is limited among Asian populations. Therefore, we investigated the factors associated with reduced HRV values in a general Japanese population by measuring HRV among the participants of the Iwaki Health Promotion Project who underwent medical examination in 2019. We performed 90-s HRV measurements in 1065 participants. Of these, we evaluated the coefficient of variation in R-R intervals (CVRR) and standard deviation in R-R intervals (SDNN). Blood was collected under a fasting condition, and investigations of glucose metabolism, lipid metabolism, renal function, liver function, advanced glycation end products, and blood pressure were performed. A multivariate regression analysis of the association between CVRR or SDNN and blood test parameters and blood pressure in 987 participants with adequately completed HRV assessments showed that reduced CVRR or SDNN was associated with higher levels of glycated hemoglobin (HbA1c), glycoalbumin, blood glucose, triglycerides, creatinine, plasma pentosidine, and diastolic blood pressure. In the general Japanese population, higher levels of HbA1c, glycoalbumin, blood glucose, triglycerides, creatinine, plasma pentosidine, and diastolic blood pressure are associated with reduced CVRR or SDNN, which are typical HRV parameters.

Medium-Term Outcomes in COVID-19.

COVID-19 causes severe illness that results in morbidity and mortality. Electrocardiographic features, including QT prolongation, have been associated with poor acute outcomes; data on the medium-term outcomes remain scarce. This study evaluated the 1-year outcomes of patients who survived the acute COVID-19 infection. Methods and Materials: Data of the 159 patients who survived the COVID-19 illness during the first wave (1 March 2020−18 May 2020) were collected. Patient demographics, laboratory findings and electrocardiography data were evaluated. Patients who subsequently died within 1-year of the index illness were compared to those who remained well. Results: Of the 159 patients who had survived the index illness, 28 (17.6%) subsequently perished within 1-year. In comparison to the patients that were alive after 1-year, the deceased were older (68 vs. 83 years, p < 0.01) and equally male (60.4% vs. 53.6%, p = 0.68), with a similar proportion of hypertension (59.5% vs. 57.1%, p = 0.68), diabetes (25.2% vs. 39.2%, p = 0.096) and ischaemic heart disease (11.5% vs. 7.1%, p = 0.54). The QTc interval for the alive and deceased patients shortened by a similar degree from the illness to post-COVID (−26 ± 33.5 vs. −20.6 ± 30.04 milliseconds, p = 0.5); the post-COVID R-R interval was longer in the alive patients compared to the deceased (818.9 ± 169.3 vs. 761.1 ± 61.2 ms, p = 0.02). A multivariate Cox regression analysis revealed that age (HR1.098 [1.045−1.153], p < 0.01), diabetes (HR3.972 [1.47−10.8], p < 0.01) and the post-COVID R-R interval (HR0.993 [0.989−0.996], p < 0.01) were associated with 1-year mortality. Conclusions: The COVID-19-associated mortality risk extends to the post-COVID period. The QTc does recover following the acute illness and is not associated with outcomes; the R-R interval is a predictor of 1-year mortality.

The Effects of Providing Advance Notice and Stress-Coping Traits on Physiological Stress of Patients during Dental Treatment.

Patients tend to feel stress in association with dental treatment due to uneasiness and fear. We investigated the effects of providing advance notice and stress-coping traits on the physiological stress of patients during dental treatment. Sixty non-dental professionals (male, n = 26; female, n = 34; mean age, 49.9 years) were recruited for this study and informed consent was obtained. Subjects were given simulated dental treatment including three stimuli, air, percussion and running of an air turbine, with or without advance notice of the stimulation during dental treatment. Real-time sympathetic nerve activity (SN) and parasympathetic nerve activity (PN) during the treatment were measured using a biological information monitor. The stress-coping traits of each subject were examined using the Lazarus-Type Stress Coping Inventory (SCI). Correlations between the nerve-activity and scores of eight stress-coping strategies of SCI and the presence/absence of advance notice were analyzed. Age, types of stimuli and order of stimuli significantly affected SN, while age, types of stimuli, and the pattern of stimulation significantly affected PN. The interaction of the stress-coping trait and presence/absence of advance notice significantly affected PN. Providing advance notice may have different effects on physiological stress depending on how the patient copes with stress.

Autonomic cardiogastric neural interaction after pulmonary vein isolation in patients with atrial fibrillation.

PURPOSE: Clinical significance of reduced vagal activity following pulmonary vein isolation (PVI) for atrial fibrillation (AF) remains unclear. Periesophageal vagal nerve injury following PVI may be a powerful contributing factor of decreased vagal tone. METHODS: Drug-refractory 51 AF patients (31 males, 64 ± 11 years), who underwent successful PVI, were enrolled. We performed esophagogastroduodenoscopy 2 days after PVI and assessed delayed gastric emptying (DGE). Additionally, the coefficient of variance of R-R interval (CVRR) as a surrogate for vagal tone was measured before PVI, as well as at 1 day and 3 months after PVI. The patients were divided into two groups, patients with DGE and patients without DGE, and changes in CVRR were compared. RESULTS: After PVI, 12 out of 51 patients (23.5%) had DGE. The baseline CVRR did not differ between the patients with (n = 12) and those without (n = 39) DGE (median 3.13%, interquartile range 1.69-5.13 vs. median 3.76%, interquartile range 2.96-5.90, P = 0.297). However, CVRR at 1 day after PVI was significantly lower in the patients with DGE than in those without (median 1.49%, interquartile range 0.90-2.19 vs. median 2.59%, interquartile range 1.58-3.86, P = 0.035), and then CVRR at 3 months became similar between the two groups, suggesting that the two groups had different changes in vagal tone after PVI. The recurrence of AF was similar at 3-6 months after PVI between the two groups. CONCLUSIONS: A significantly decreased CVRR immediately after PVI is a sign of DGE incidence, implying collateral damage to the esophagus.

Decline in renal function associated with cardiovascular autonomic neuropathy positively coordinated with proteinuria in patients with type 2 diabetes.

AIMS/INTRODUCTION: To investigate the association between cardiovascular autonomic neuropathy (CAN) assessed by the coefficient of variation of the R-R interval and the reduction in the estimated glomerular filtration rate (eGFR) in patients with type 2 diabetes. MATERIALS AND METHODS: This retrospective observational cohort study enrolled type 2 diabetes patients who had their coefficient of variation of the R-R interval measured on an electrocardiogram from January 2005 to December 2018. CAN was defined using the reference coefficient of variation of the R-R interval value based on age and sex. The primary outcome was set as a 40% eGFR decline from baseline. Regression analyses using the Cox proportional hazards model were carried out to evaluate the association. RESULTS: Of the 831 patients, 118 (14.2%) were diagnosed with CAN. In the analysis of the primary outcome, the median follow-up period was 5.3 years, and 25 (21.2%) patients with CAN and 78 (10.9%) patients without CAN developed a 40% eGFR decline. In the univariate regression analysis, CAN was significantly associated with a 40% eGFR decline (hazard ratio 2.42, 95% confidence interval 1.54-3.80). In the multivariate analysis, CAN remained almost significant after adjusting for the prognostic risk factors for CAN and the decline in the renal function, and an interaction with proteinuria was found. In analyses for the interaction effect between CAN and proteinuria, the presence of CAN synergistically increased the risk of an eGFR decline in patients with macroproteinuria. CONCLUSIONS: CAN strongly increased the risk of a 40% eGFR decline from baseline, especially in type 2 diabetes patients with macroproteinuria.

[A preliminary report on the variation of respiratory heart rate during sleep in normal subjects and patients with chronic diseases without sleep apnea].

Objective: The new theory of holistic integrative physiology and medicine, which describes the integrative regulation of respiratory, circulatory and metabolic systems in human body, generates the hypothesis of that breath is the origin of variability of circulatory parameters. We investigated the origin of heart rate variability by analyzing relationship between the breath and heart rate variability (HRV) during sleep. Methods: This retrospective study analyzed 8 normal subjects (NS) and 10 patients of chronic diseases without sleep apnea (CDs-no-SA). After signed the informed consent form, they performed cardiopulmonary exercise testing (CPET) in Fuwai Hospital and monitored polysomnography (PSG) and electrocardiogram (ECG) during sleep since 2014. We dominantly analyzed the correlation between the respiratory cycle during sleep and the heart rate variability cycle of the ECG R-R interval. The HRV cycle included the HR increase from the lowest to the highest and decrease from the highest to the lowest point. The number of HRV (HRV-n), average HRV time and other parameters were calculated. The breath cycle included complete inhalation and subsequent exhalation. The number of breath (B-n), average breath time and other breath parameters were analyzed and calculated. We analyzed each person's relationship between breath and HRV; and the similarities and differences between the NS and CDs-no-SA groups. Independent sample t test was used for statistical analysis, with P<0.05. Results: CPET core parameter such as Peak VO2 (83.8±8.9)% in NS were significantly higher than that (70.1±14.9)% in patients of chronic diseases without sleep apnea (P<0.05), but there was no difference between their AHI (1.7±1.3) in NS and AHI (2.9±1.2) in CDs-no-SA (P>0.05). The B-n and the HRV-n (6581.63±1411.90 vs 6638.38±1459.46), the average B time and the average HRV time (4.19±0.57)s vs (4.16±0.62)s in NS were similar without significant difference (P>0.05). The comparison of the numbers in CDs-no-SA were the number (7354.50±1443.50 vs 7291.20±1399.31) and the average times ((4.20±0.69)s vs (4.23±0.68)s) of B and HRV were similar without significant difference (P>0.05). The ratios of B-n/HRV-n in NS and CDs-no-SA were (0.993±0.027 vs 1.008±0.024) and both were close to 1 and similar without significant difference (P>0.05). The average magnitude of HRV in NS ((5.74±3.21) bpm) was significantly higher than that in CDs-no-SA ((2.88±1.44) bpm) (P<0.05). Conclusion: Regardless of the functional status of NS and CDs-no-SA, there is a similar consistency between B and HRV. The origin of initiating factors of HRV is the respiration.

Short-term heart rate variability in resting conditions: methodological considerations.

Low values on heart rate variability (HRV) derived parameters at resting have been used to predict cardiovascular diseases (CVD) and mortality. In this regard, short-term HRV recordings (usually from 5 to 15 minutes) are increasing their popularity because data acquisition can be performed under more controlled conditions than long-term recordings (e.g., 24 hours). However, different methodological aspects before, during, and after the HRV assessment could affect the quantification and the clinical interpretations of the HRV-derived parameters, as well as hamper comparisons across different studies. In the present study, we summarize these methodological aspects that should be considered in both the research and the clinical settings. These are: (1) the validity and reproducibility of the device used to assess the HRV; (2) the influence of the software used to perform the artefact correction; (3) previous conditions before the testing day; (4) establishing the proper conditions during the HRV assessment (e.g., controlled respiratory frequency); (5) after assessing the HRV, considering the "best" data selection and statistical analysis approach; and (6) the role of the heart rate on the associations between the different CVD risk factors outcomes (e.g., cardiorespiratory fitness) and the HRV-derived parameters.

Electrophysiological investigation for autonomic dysfunction in patients with myasthenia gravis: A prospective study.

BACKGROUND AND PURPOSE: Myasthenia gravis (MG) is an autoimmune disorder of neuromuscular transmission. Autonomic dysfunction is not a commonly known association with MG. We conducted this study to evaluate autonomic functions in MG & subgroups and to investigate the effects of acetylcholinesterase inhibitors. METHODS: This study comprised 30 autoimmune MG patients and 30 healthy volunteers. Autonomic tests including sympathetic skin response (SSR) and R-R interval variation analysis (RRIV) was carried out. The tests were performed two times for patients who were under acetylcholinesterase inhibitors during the current assessment. RESULTS: The RRIV rise during hyperventilation was better (p=0.006) and Valsalva ratio (p=0.039) was lower in control group. The SSR amplitudes were lower thereafter drug intake (p=0.030). As much as time went by after drug administration prolonged SSR latencies were obtained (p=0.043).Valsalva ratio was lower in the AchR antibody negative group (p=0.033). CONCLUSION: The findings showed that both ocular/generalized MG patients have a subclinical parasympathetic abnormality prominent in the AchR antibody negative group and pyridostigmine has a peripheral sympathetic cholinergic noncumulative effect.

Multi-Chaotic Analysis of Inter-Beat (R-R) Intervals in Cardiac Signals for Discrimination between Normal and Pathological Classes.

Cardiac signals have complex structures representing a combination of simpler structures. In this paper, we develop a new data analytic tool that can extract the complex structures of cardiac signals using the framework of multi-chaotic analysis, which is based on the p-norm for calculating the largest Lyapunov exponent (LLE). Appling the p-norm is useful for deriving the spectrum of the generalized largest Lyapunov exponents (GLLE), which is characterized by the width of the spectrum (which we denote by W). This quantity measures the degree of multi-chaos of the process and can potentially be used to discriminate between different classes of cardiac signals. We propose the joint use of the GLLE and spectrum width to investigate the multi-chaotic behavior of inter-beat (R-R) intervals of cardiac signals recorded from 54 healthy subjects (hs), 44 subjects diagnosed with congestive heart failure (chf), and 25 subjects diagnosed with atrial fibrillation (af). With the proposed approach, we build a regression model for the diagnosis of pathology. Multi-chaotic analysis showed a good performance, allowing the underlying dynamics of the system that generates the heart beat to be examined and expert systems to be built for the diagnosis of cardiac pathologies.

Adults' Stress Response to Unexpected Oral and Arithmetic Tasks in Supine Position.

To study the autonomic nervous system (ANS) and hypothalamus pituitary adrenal axis (HPA) response before and after mental stress test in healthy adolescents and adults, is the aim of this study. Twenty healthy adults (aged 23-46 years) entered the Trier Social Stress Test (TSST), after informed consent signing. The procedure was modified: (a) the participants' position was supine as ANS system changes were to be assessed, (b) the interviewers were entering and departing from the session room. Salivary cortisol (marker of HPA axis response) samples were collected at the end of the baseline and 20 min after TSST. ANS of the heart was measured with CNS Task Force Monitor in supine position and was recorded during relaxation (15 min) and after TSST. The sympathovagal balance (LF/HF ratio) for each phase was computed. Evaluations were conducted with R. The HPA axis disturbance between baseline and 20 min after TSST was significant (g = 0.545 [0.092, 0.999]) and in adolescents (whereas, the mean intervals of the sinus rhythm RR parameter were found largely changed (g = 0.834 [0.340, 1.327]). The sympathovagal balance component of heart rate variability LF/HF ratio was founded unchanged (g = 0.215 [-0.211, 0.641]). RR changes were not correlated to salivary cortisol concentrations at any phase. Mean RRIs and salivary cortisol levels were significantly increased, although HPA axis showed medium size effect. However, the systems effectively counterbalance the perturbation, since the LF/HF ratio does not change. Our findings suggest further research in stress effect on HPA and ANS cross-talk and dynamics.