Nonlinear Heart Rate Variability Indices Research Articles

Determinants of the heart rate variability in type 1 diabetes mellitus.

Evaluation of heart rate variability (HRV) detects the early subclinical alterations of the autonomic nervous system. Thus, impaired HRV is the earliest subclinical marker of cardiac autonomic neuropathy (CAN) in type 1 diabetes mellitus (T1DM). We aimed to explore the HRV parameters in asymptomatic T1DM patients and compare them with the results obtained in healthy subjects. Potential associations between HRV parameters and the established risk factors for CAN and cardiovascular diseases were also investigated. Seventy T1DM patients (38 ± 12 years, 46 females) and 30 healthy subjects were enrolled into the study. For HRV analysis, beat-to-beat heart rate was recorded for 30min. The less noisy 5-min segment of the recording was analyzed by Bittium Cardiac Navigator HRV analysis software. Time domain, frequency domain, and nonlinear indices were calculated. Regarding ratio of low to high frequency component (LF/HF), no differences were found between the two populations (p = 0.227). All the further, time domain, frequency domain, and nonlinear HRV indices were significantly lower in T1DM patients (each p < 0.001). In multiple linear models, disease duration remained the only independent predictor of LF/HF ratio (p = 0.019). HbA1c was found to be significant independent predictor of all further time domain (SDNN, p < 0.001; rMSSD, p < 0.001), frequency domain (VLF, p < 0.001; LF, p = 0.002; HF, p = 0.006; Total Power, p = 0.002), and nonlinear indices (SD1, p = 0.006; SD2, p = 0.007), alone, or in combination with other factors, such as age or body mass index. Asymptomatic T1DM patients have significantly reduced overall HRV as compared with healthy subjects, indicating subclinical CAN. Quality of the glycemic control is important determinant of HRV among T1DM patients. This relationship is independent of other risk factors for CAN or cardiovascular diseases.

Heart rate variability at rest and in response to stress: Comparative study between hemodialysis and peritoneal dialysis patients.

Cardiac arrhythmias and sudden death are the leading causes of mortality in end-stage kidney disease (ESKD). Autonomic nervous system (ANS) dysfunction contributes to this arrhythmogenic background. This study compared heart rate variability (HRV) indices between hemodialysis (HD) and peritoneal dialysis (PD) patients, both at rest and in response to mental and physical stimulation maneuvers. Thirty-four HD and 34 PD patients matched for age, sex, and dialysis vintage, and 17 age- and sex-matched controls were studied. ANS function was examined by linear and non-linear HRV indices. Heart rate was recorded continuously (Finometer-PRO) at rest and during ANS maneuvers (orthostatic, mental-arithmetic, sit-to-stand, handgrip exercise tests). At rest, no significant differences between HD and PD were observed in HRV (root mean square of successive differences [RMSSD]: HD = 57.1 ± 81.1 vs PD = 69.6 ± 113.4 ms; P = 0.792), except for detrended fluctuation analysis (DFA-α1) (HD = 0.87 ± 0.40 vs PD = 0.70 ± 0.20; P = 0.047). DFA-α1 was significantly lower in PD than controls (1.00 ± 0.33; P < 0.05). All HRV indices during the mental-arithmetic test (RMSSD: HD = 128.2 ± 346.0 vs PD = 87.5 ± 150.0 ms; P = 0.893) and the physical stress tests were similar between HD and PD. The standard deviation along the line-of-identity (SD2)/the standard deviation perpendicular to the line-of-identity (SD1) ratio during mental-arithmetic was marginally lower in HD and significantly lower in PD than controls (PD = 1.31 ± 0.47 vs controls = 1.79 ± 0.64; P < 0.05). Both dialysis groups presented similar patterns in HRV responses during orthostatic and handgrip exercise tests. After the sit-to-stand, RMSSD, SD1, SD2, and DFA-α2 were higher compared to rest only in HD (RMSSD = 57.1 ± 81.1 vs 126.7 ± 185.7 ms; P = 0.028), suggesting a greater difficulty of HD patients in recovering normal ANS function in response to physical stress. In conclusion, HRV indices at rest and after mental and physical stimulation did not differ between HD and PD; however, the ANS responses following the sit-to-stand test were more impaired in HD. These findings suggest that ANS dysfunction is not largely affected by dialysis modality, but small differences in normal ANS recovery may exist.

HEMODIALYSIS EFFECTS ON AUTONOMIC FUNCTION: RESULTS OF LINEAR AND NON-LINEAR ANALYSIS OF HEART-RATE-VARIABILITY AT REST AND IN RESPONSE TO PHYSICAL AND MENTAL STRESS TESTS

Objective: Cardiac arrhythmias are the most common cause of death in hemodialysis. Autonomic dysfunction plays a central role in this arrhythmogenic background. Previous studies on hemodialysis-related changes in heart-rate-variability(HRV) give contradictory results. This study investigated HRV indices both at rest and in response to physical and mental stimulation maneuvers at multiple time-points around and during the hemodialysis procedure. Design and method: Autonomic function was assessed by linear and non-linear HRV indices at pre-dialysis, during-dialysis(3 equal time-periods), post-dialysis, and on the non-dialysis day in 36 hemodialysis patients. Continuous measurement of beat-by-beat heart-rate was recorded with Finometer-PRO(The Netherlands) at rest and after orthostatic, sit-to-stand, handgrip and mental-arithmetic test. Results: The RMSSD, SD1, and SD2 indices significantly increased during dialysis(early-HD, mid-HD, late-HD periods) compared with the pre-dialysis levels(p&lt;0.05) and returned to baseline post-dialysis(RMSSD: 54.39±83.73 vs 137.98±109.53* vs 119.85±97.34* vs 144.47±88.74* vs 85.82±121.43msec, *p&lt;0.05 vs pre-dialysis and post-dialysis). No differences were detected in the above indices between the pre-dialysis and non-dialysis day. However, post-dialysis, the HRV responses to orthostatic and sit-to-stand tests were more exaggerated than in the pre-dialysis measurements (p&lt;0.05). The HRV responses both at resting and physical tests in the non-dialysis day were similar to the pre-dialysis levels. HRV indices in mental-arithmetic test during hemodialysis were much higher than at the non-dialysis day(RMSSD: 77.05 (180.41) vs 19.75 (105.47)msec; p = 0.031) were detected. Conclusions: Hemodialysis causes marked changes in autonomic function. Resting HRV indices return to baseline post-dialysis, but HRV responses to physical stress remain exaggerated and return to baseline on the non-dialysis day. Detecting patients with significant autonomic dysfunction may help towards reduction of arrhythmia risk through individualized approaches.

Heart Rate Variability Analysis on Electrocardiograms, Seismocardiograms and Gyrocardiograms of Healthy Volunteers and Patients with Valvular Heart Diseases.

Heart rate variability (HRV) is the physiological variation in the intervals between consecutive heartbeats that reflects the activity of the autonomic nervous system. This parameter is traditionally evaluated based on electrocardiograms (ECG signals). Seismocardiography (SCG) and/or gyrocardiography (GCG) are used to monitor cardiac mechanical activity; therefore, they may be used in HRV analysis and the evaluation of valvular heart diseases (VHDs) simultaneously. The purpose of this study was to compare the time domain, frequency domain and nonlinear HRV indices obtained from electrocardiograms, seismocardiograms (SCG signals) and gyrocardiograms (GCG signals) in healthy volunteers and patients with valvular heart diseases. An analysis of the time domain, frequency domain and nonlinear heart rate variability was conducted on electrocardiograms and gyrocardiograms registered from 29 healthy male volunteers and 30 patients with valvular heart diseases admitted to the Columbia University Medical Center (New York City, NY, USA). The results of the HRV analysis show a strong linear correlation with the HRV indices calculated from the ECG, SCG and GCG signals and prove the feasibility and reliability of HRV analysis despite the influence of VHDs on the SCG and GCG waveforms.

Linear and Non-Linear Heart Rate Variability Indexes from Heart-Induced Mechanical Signals Recorded with a Skin-Interfaced IMU.

Heart rate variability (HRV) indexes are becoming useful in various applications, from better diagnosis and prevention of diseases to predicting stress levels. Typically, HRV indexes are retrieved from the heart's electrical activity collected with an electrocardiographic signal (ECG). Heart-induced mechanical signals recorded from the body's surface can be utilized to record the mechanical activity of the heart and, in turn, extract HRV indexes from interbeat intervals (IBIs). Among others, accelerometers and gyroscopes can be used to register IBIs from precordial accelerations and chest wall angular velocities. However, unlike electrical signals, the morphology of mechanical ones is strongly affected by body posture. In this paper, we investigated the feasibility of estimating the most common linear and non-linear HRV indexes from accelerometer and gyroscope data collected with a wearable skin-interfaced Inertial Measurement Unit (IMU) positioned at the xiphoid level. Data were collected from 21 healthy volunteers assuming two common postures (i.e., seated and lying). Results show that using the gyroscope signal in the lying posture allows accurate results in estimating IBIs, thus allowing extracting of linear and non-linear HRV parameters that are not statistically significantly different from those extracted from reference ECG.

Hemodialysis Effects on Autonomic Function: Results of Linear and Nonlinear Analysis of Heart Rate Variability at Rest and in Response to Physical and Mental Stress Tests

Introduction: Cardiac arrhythmias are the most common cause of death in hemodialysis. Autonomic dysfunction plays a central role in this arrhythmogenic background. Previous studies on hemodialysis-related changes in heart rate variability (HRV) give contradictory results. This study investigated HRV indices both at rest and in response to physical and mental stimulation maneuvers at multiple time-points around and during the hemodialysis procedure. Methods: Autonomic function was assessed by linear and nonlinear HRV indices at predialysis, during dialysis (3 equal time-periods), postdialysis, and on the nondialysis day in 36 hemodialysis patients. Continuous measurement of beat-by-beat heart rate was recorded with Finometer-PRO (The Netherlands) at rest and after orthostatic, sit-to-stand, handgrip, and mental-arithmetic test. Results: The RMSSD, SD1, and SD2 indices significantly increased during dialysis (early-HD, mid-HD, late-HD periods) compared with the predialysis levels (p < 0.05) and returned to baseline postdialysis (RMSSD: 54.39 ± 83.73 vs. 137.98 ± 109.53* vs. 119.85 ± 97.34* vs. 144.47 ± 88.74* vs. 85.82 ± 121.43msec, *p < 0.05 vs. predialysis and postdialysis). No differences were detected in the above indices between the predialysis and nondialysis day. However, postdialysis, the HRV responses to orthostatic and sit-to-stand tests were more exaggerated than in the predialysis measurements (p < 0.05). The HRV responses both at resting and physical tests in the nondialysis day were similar to the predialysis levels. HRV indices in the mental arithmetic test during hemodialysis were much higher than at the nondialysis day (RMSSD: 77.05 [180.41] versus 19.75 [105.47] msec; p = 0.031). Conclusions: Hemodialysis causes marked changes in the autonomic function. Resting HRV indices return to baseline postdialysis, but HRV responses to physical stress remain exaggerated and return to baseline on the nondialysis day. Detecting patients with significant autonomic dysfunction may help towards reduction of arrhythmia risk through individualized approaches.

Dysfunction of the cardiac parasympathetic system in fatal familial insomnia: a heart rate variability study.

Although sympathetic hyperactivity with preserved parasympathetic activity has been extensively recognized in fatal familial insomnia (FFI), the symptoms of parasympathetic nervous system failure observed in some patients are difficult to explain. Using heart rate variability (HRV), this study aimed to discover evidence of parasympathetic dysfunction in patients with FFI and the difference of parasympathetic activity between patients with FFI and Creutzfeldt-Jakob disease (CJD). This study enrolled nine patients with FFI, eight patients with CJD and 18 healthy controls (HCs) from May 2013 to August 2020. All participants underwent a nocturnal video-polysomnography with lead II electrocardiography, and the data were analyzed using linear and nonlinear indices of HRV during both wake and sleep states. Compared to the HC and CJD groups, the FFI group had a continuously higher heart rate with a lower amplitude of oscillations. The low frequency (LF)/high frequency (HF) ratio and ratio of SD1 to SD2 and correlation dimension D2 (CD2) were significantly different in the FFI group compared to the HC group. The root mean square of successive differences (RMSSD), HF and SD1 in the FFI group were significantly lower than in the HC group. RMSSD, SD1, and CD2 in the FFI group were all significantly lower than in the CJD group. Cardiovascular dysautonomia in FFI may be partly attributable to parasympathetic abnormalities, not just sympathetic activation. HRV may be helpful as a noninvasive, quantitative, and effective autonomic function test for FFI diagnosis.

Contactless Monitoring of Heart Rate Variability During Respiratory Maneuvers

Heart rate variability (HRV) is a noninvasive marker for the cardiovascular system and the substantial influence of this system on the autonomous nervous system (ANS). Contact and remote photoplethysmography (PPG) proved to be a reliable means of pulse rate variability (PRV) measurement as in wearable devices or imaging PPG using video cameras with evolved technical specifications. However, PRV effectiveness remains unclear during controlled breathing rate. Specifically, respiratory rate, among other physiological factors, applies profound effects on ANS balance. In this study, we demonstrated that PRV can be a reliable marker, as HRV, during various controlled breathing rates. We evaluated the proposed PRV monitoring study against reference HRV obtained from an ECG measurement device. PRV was measured from video streams captured using a smartphone and a webcam for the upper abdominal section of healthy volunteers while in standing position and performing six different respiratory maneuvers. We evaluated frequency and nonlinear HRV indices. Agreement between all indices was tested for camera-based devices and ground truth for all performed tasks. The agreement presented a consistent mean close to 95% limit of agreement (LoA). Also, we employed spectral analysis and measured the spectral divergences, normalized root mean squared error (NRMSE), and correlation. Kullback-Leibler Divergence median and percentiles results indicate congruent spectrums, where the maximum median was 0.18. A significant spectral correlation with minimum value of 0.98, and relatively low spectrum NRMSE of 0.24 were observed. Moreover, the results led to HRV physiological related phenomena which agreed with physiologically interpretations found in the literature.

Quantification of Cardiovascular Regulation Applying Heart Rate Variability Analyses for Different Warm and Moist Chest Compresses in Healthy Subjects.

Background: In integrative medicine, complementary healing methods, such as external applications (massages, rhythmic rubs, and compresses), are part of the practice and clinical application and have proven their therapeutic effect in various fields. Objective: Aim of this exploratory, controlled, single-blinded study was to investigate the effects of three different warming chest compresses on cardiovascular regulation by analyzing heart rate variability (HRV) in healthy subjects. Methods: Over a period of 4 weeks, three different warming chest compresses (a hot water compress, a ginger powder compress, and a mustard flour compress) in 30 healthy subjects were analyzed. For all subjects, 48-h long-term electrocardiograms were recorded, and afterward, epochs of 5 min length extracted and analyzed by different linear and nonlinear HRV indices. Results: A moist chest compress did not result in any significant short- and long-term stimulation of the autonomic regulation, except for a short-term significant decrease in heart rate (meanNN, p < 0.05). Warm and moist chest compresses with ginger flour led to significantly increased HRV (sdNN, p < 0.05; symbolic dynamics2, p < 0.05) and its complexity (renyi4 entropy, p < 0.05) and a significant decrease in heart rate (meanNN, p < 0.00036), and thus to a short-term relaxation effect. In contrast, warm and moist chest compresses with mustard flour led to significantly decreased HRV and their complexity (time-, frequency-, and nonlinear dynamics domain, p < 0.00036), which can be interpreted as a stress reaction of the autonomous nervous system. Conclusions: The application of chest compresses led to short-term relaxation effects (ginger) as well as short-term stress effects (mustard) but not to any significant longer-term effect on HRV in healthy subjects.

High-intensity interval training versus moderate-intensity continuous training on cardiac autonomic control in hypertensive patients

Aim: This study aims to verify and compare the acute and chronic effects of high-intensity interval training and moderate-intensity continuous training sessions on the linear and nonlinear heart rate variability indexes, responses of blood pressure, aerobic power, aerobic capacity, and quality of life from patients with systemic arterial hypertension. Methods: Controlled, randomized clinical trial with intention-to-treat analysis. Non-alcoholic, non-diabetic patients between 18 and 60 years of age, with a diagnosis of prehypertension or stage I hypertension for at least 12 months and with controlled blood pressure levels. Conclusion: This protocol study intends to show that high-intensity interval exercise in controlled hypertensive patients with low cardiovascular risk has a greater hypotensive effect, as well as an increase in vagal modulation on the heart.

Assessment of cardiac autonomic function in patients with permanent and paroxysmal atrial fibrillation

Abstract Background Atrial fibrillation (AF) is the commonest abnormal heart rhythm with significant related morbidity and mortality. There is increasing evidence that abnormalities of the cardiac autonomic nervous system (ANS) are involved in the pathogenesis of AF. Exploring the ANS is possible through heart rate variability (HRV) evaluation. Purpose To investigate whether HRV is more abnormal in patients with permanent AF compared to paroxysmal AF. Design In a cross-sectional comparison, we studied two patient groups: permanent AF (n=30) and paroxysmal AF (n=31). Time-domain, frequency-domain and non-linear measures of HRV were determined using eMotion Faros ECG sensor. Participant's breathing was controlled with a metronome set at 12 breaths per minute. Data was analysed using SPSS software. Results Time-domain and non-linear indices of HRV were significant higher in permanent AF group compared to paroxysmal AF (table 1). Permanent AF was the only independent predictor of HRV on multivariable analysis in this cohort of patients (p=0.006) Conclusions First study investigating autonomic function in patients with permanent AF and paroxysmal AF. HRV indices were significantly higher in permanent AF compared to paroxysmal AF which may suggest pronounced cardiac autonomic influence in the pathophysiology of permanent AF. Funding Acknowledgement Type of funding sources: None.

Использование нелинейных параметров вариабельности сердечного ритма для выявления стресса

This paper presents a stress detection algorithm using heart rate variability (HRV) parameters. Five-minute electrocardiograms were recorded at rest and under exam stress (252 students were involved). The determined HRV parameters were applied to detect stress by means of several classification algorithms. We analysed linear indices in the time (standard deviation of NN intervals (SDNN) and root mean square of successive RR interval differences (RMSSD)) and frequency domains (low frequency (LF) and high frequency (HF) power as well as LF/HF ratio). To study nonlinear HRV indices, we evaluated approximate entropy (ApEn), sample entropy (SampEn), α1 (DFA1) and α2 (DFA2) scaling exponents, correlation dimension D2, and recurrence plot quantification measures (recurrence rate (REC), mean diagonal line length (Lmean), maximum diagonal line length (Lmax), determinism (DET), and Shannon entropy (ShanEn)). Receiver operating characteristic (ROC) was used to test the performance of the classifiers derived from HRV. The highest area under the ROC curve (AUC), sensitivity, and specificity were found for mean RR-interval, DFA1, DFA2, RMSSD, and Lmax. These parameters were used for stress/rest classification with the help of algorithms that are common in clinical and physiological applications, i.e. logistic regression (LR) and linear discriminant analysis (LDA). Classification performance for stress was quantified using accuracy, sensitivity and specificity measures. The LR achieved an accuracy of 68.25 % at an optimal cutoff value of 0.57. LDA determined stress with 67.46 % accuracy. Thus, HRV parameters can serve as an objective tool for stress detection.

Autonomic responses to facial expression tasks in children with autism spectrum disorders: Cross-section study

BackgroundThe autonomic nervous system has an influence on emotions and behavior modulation, however, the relationship between autonomic modulation impairment and the autism spectrum disorder (ASD) is yet to be fully described. AimsTo evaluate the autonomic responses of children with and without ASD through the non-linear, and linear heart rate variability (HRV) measures, and assess the correlation between these responses, the severity and behavioral symptoms of autism. Methods and procedures27 children diagnosed with ASD (EG = experimental group) and 28 matching controls (CG = control group) were evaluated. The HRV was evaluated in 15 min sections at the following moments: I) Resting condition; II) During facial expression tasks; and III) Recovery. The severity and behavioral symptoms of autism were evaluated by the Childhood Autism Rating Scale (CARS) and Autistic Behaviors Checklist (ABC) scales. Outcomes and resultsThe facial expression tasks influenced the activity of the autonomic nervous system in both groups, however the EG experienced more autonomic changes. These changes were mostly evidenced by the non-linear indices. Also, the CARS and ABC scales showed significant correlations with HRV indices. Conclusions and implicationsChildren with ASD presented an autonomic modulation impairment, mostly identified by the non-linear indices of HRV. Also, this autonomic impairment is associated with the severity and behavioral symptoms of autism.

Preoperative Heart Rate Variability During Sleep Predicts Vagus Nerve Stimulation Outcome Better in Patients With Drug-Resistant Epilepsy.

Objective: Vagus nerve stimulation (VNS) is an adjunctive and well-established treatment for patients with drug-resistant epilepsy (DRE). However, it is still difficult to identify patients who may benefit from VNS surgery. Our study aims to propose a VNS outcome prediction model based on machine learning with multidimensional preoperative heart rate variability (HRV) indices.Methods: The preoperative electrocardiography (ECG) of 59 patients with DRE and of 50 healthy controls were analyzed. Responders were defined as having at least 50% average monthly seizure frequency reduction at 1-year follow-up. Time domain, frequency domain, and non-linear indices of HRV were compared between 30 responders and 29 non-responders in awake and sleep states, respectively. For feature selection, univariate filter and recursive feature elimination (RFE) algorithms were performed to assess the importance of different HRV indices to VNS outcome prediction and improve the classification performance. Random forest (RF) was used to train the classifier, and leave-one-out (LOO) cross-validation was performed to evaluate the prediction model.Results: Among 52 HRV indices, 49 showed significant differences between DRE patients and healthy controls. In sleep state, 35 HRV indices of responders were significantly higher than those of non-responders, while 16 of them showed the same differences in awake state. Low-frequency power (LF) ranked first in the importance ranking results by univariate filter and RFE methods, respectively. With HRV indices in sleep state, our model achieved 74.6% accuracy, 80% precision, 70.6% recall, and 75% F1 for VNS outcome prediction, which was better than the optimal performance in awake state (65.3% accuracy, 66.4% precision, 70.5% recall, and 68.4% F1).Significance: With the ECG during sleep state and machine learning techniques, the statistical model based on preoperative HRV could achieve a better performance of VNS outcome prediction and, therefore, help patients who are not suitable for VNS to avoid the high cost of surgery and possible risks of long-term stimulation.

BioSignal modelling for prediction of cardiac diseases using intra group selection method

The Autonomous Nervous System (ANS) controls the nervous system and Heart Rate Variability (HRV) can be used as a diagnostic tool to diagnose heart defects. HRV can be classified into linear and nonlinear HRV indices which are used mostly to measure the efficiency of the model. For prediction of cardiac diseases, the selection and extraction features of machine learning model are effective. The available model used till date is based on HRV indices to predict the cardiac diseases accurately. The model could hardly throw light on specifics of indices, selection process and stability of the model. The proposed model is developed considering all facet electrocardiogram amplitude (ECG), frequency components, sampling frequency, extraction methods and acquisition techniques. The machine learning based model and its performance shall be tested using the standard BioSignal method, both on the data available and on the data obtained by the author. This is unique model developed by considering the vast number of mixtures sets and more than four complex cardiac classes. The statistical analysis is performed on a variety of databases such as MIT/BIH Normal Sinus Rhythm (NSR), MIT/BIH Arrhythmia (AR) and MIT/BIH Atrial Fibrillation (AF) and Peripheral Pule Analyser using feature compatibility techniques. The classifiers are trained for prediction with approximately 40000 sets of parameters. The proposed model reaches an average accuracy of 97.87 percent and is sensitive and précised. The best features are chosen from the different HRV features that will be used for classification. The present model was checked under all possible subject scenarios, such as the raw database and the non-ECG signal. In this sense, robustness is defined not only by the specificity parameter, but also by other measuring output parameters. Support Vector Machine (SVM), K-nearest Neighbour (KNN), Ensemble Adaboost (EAB) with Random Forest (RF) are tested in a 5% higher precision band and a lower band configuration. The Random Forest has produced better results, and its robustness has been established.

Application of the Variance Delay Fuzzy Approximate Entropy for Autonomic Nervous System Fluctuation Analysis in Obstructive Sleep Apnea Patients.

Obstructive sleep apnea (OSA) is a fatal respiratory disease occurring in sleep. OSA can induce declined heart rate variability (HRV) and was reported to have autonomic nerve system (ANS) dysfunction. Variance delay fuzzy approximate entropy (VD_fApEn) was proposed as a nonlinear index to study the fluctuation change of ANS in OSA patients. Sixty electrocardiogram (ECG) recordings of the PhysioNet database (20 normal, 14 mild-moderate OSA, and 26 severe OSA) were intercepted for 6 h and divided into 5-min segments. HRV analysis were adopted in traditional frequency domain, and nonlinear HRV indices were also calculated. Among these indices, VD_fApEn could significantly differentiate among the three groups (p < 0.05) compared with the ratio of low frequency power and high frequency power (LF/HF ratio) and fuzzy approximate entropy (fApEn). Moreover, the VD_fApEn (90%) reached a higher OSA screening accuracy compared with LF/HF ratio (80%) and fApEn (78.3%). Therefore, VD_fApEn provides a potential clinical method for ANS fluctuation analysis in OSA patients and OSA severity analysis.

Heart rate variability in patients with atrial fibrillation and hypertension.

Atrial fibrillation (AF) and hypertension are independently associated with impaired autonomic function determined using heart rate variability (HRV). As these conditions frequently co-exist, we sought to determine whether AF would worsen HRV in hypertensive patients. We studied HRV in AF (and hypertension) (n=61) and hypertension control group (n=33). The AF (and hypertension) group was subdivided into permanent AF (n=30) and paroxysmal AF (n=31) and re-studied. Time-domain, frequency-domain and nonlinear measures of HRV were determined. Permanent AF group (n=30) was followed up after 8weeks following optimisation of their heart rate and blood pressure (BP). Time-domain and nonlinear indices of HRV were higher in AF (and hypertension) group compared to hypertensive controls (P≤.01). Time-domain and nonlinear indices of HRV were higher in permanent AF group compared to paroxysmal AF (P≤.001). Permanent AF was an independent predictor of HRV on multivariable analysis (P=.006). Optimisation of heart rate and BP had no significant impact on HRV in permanent AF. AF, independent of hypertension, is characterised with marked HRV and is possibly related to vagal tone. HRV is higher in permanent AF compared to paroxysmal AF suggesting evident autonomic influence in the pathophysiology of permanent AF. Modulation of autonomic influence on cardiovascular system should be explored in future studies.

Impact of exercise in high-humidity on heart rate variability and salivary oxidative stress in obese and lightweight asthmatic children.

Asthma and obesity are becoming increasingly common among children. Such conditions are known to negatively affect both cardiac autonomic function and oxidative stress. We therefore investigated the heart rate variability (HRV) and oxidative (malondialdehyde, MDA) response to exercise within a high humidity environment (~65%) in obese and lightweight asthmatic children. Forty-two children participated in this study and were categorized into four groups: obese asthmatic (OA, N.=10), obese non-asthmatic (ONA, N.=15), lightweight asthmatic (LA, N.=10), and lightweight non-asthmatic (LNA, N.=7). Time-domain and nonlinear indices of HRV were assessed at rest, during, and immediately after exercise. Further, saliva samples were collected immediately before and after exercise and analyzed for the determination of MDA. HRV significantly decreased during and after exercise compared to baseline (P<0.05) with short-term fractal scaling exponent (α1) for the LNA group significantly smaller than the OA group after exercise (P<0.05). In contrast, the long-term fractal scaling exponent (α2) was greater after exercise compared to baseline and during exercise for all groups (P<0.05). MDA significantly decreased after exercise compared to baseline (P<0.05). We also found significant correlations after exercise between salivary levels of MDA with HRV components (i.e., RMSSD, SD1, and α2) in asthmatic groups (all P<0.05). Our findings showed that exercise in high humidity environment does not significantly differentiate the autonomic response among children with various conditions (i.e., obese, asthmatic and healthy). However, a significant relationship was found between HRV and MDA in asthmatic children after exercise, highlighting the inter-relationship between oxidative stress markers and autonomic function in asthmatic children.

Association between Mean Heart Rate and Recurrence Quantification Analysis of Heart Rate Variability in End-Stage Renal Disease.

Linear heart rate variability (HRV) indices are dependent on the mean heart rate, which has been demonstrated in different models (from sinoatrial cells to humans). The association between nonlinear HRV indices, including those provided by recurrence plot quantitative analysis (RQA), and the mean heart rate (or the mean cardiac period, also called meanNN) has been scarcely studied. For this purpose, we analyzed RQA indices of five minute-long HRV time series obtained in the supine position and during active standing from 30 healthy subjects and 29 end-stage renal disease (ESRD) patients (before and after hemodialysis). In the supine position, ESRD patients showed shorter meanNN (i.e., faster heart rate) and decreased variability compared to healthy subjects. The healthy subjects responded to active standing by shortening the meanNN and decreasing HRV indices to reach similar values of ESRD patients. Bivariate correlations between all RQA indices and meanNN were significant in healthy subjects and ESRD after hemodialysis and for most RQA indices in ESRD patients before hemodialysis. Multiple linear regression analyses showed that RQA indices were also dependent on the position and the ESRD condition. Then, future studies should consider the association among RQA indices, meanNN, and these other factors for a correct interpretation of HRV.

Nonlinear heart rate variability biomarkers for gastric cancer severity: A pilot study

Identifying prognostic factors by affordable tools is crucial for guiding gastric cancer (GC) treatments especially at earlier stages for timing interventions. The autonomic function that is clinically assessed by heart rate variability (HRV) is involved in tumorigenesis. This pilot study was aimed to examine whether nonlinear indices of HRV can be biomarkers of GC severity. Sixty-one newly-diagnosed GC patients were enrolled. Presurgical serum fibrinogen (FIB), carcinoembryonic antigen (CEA), and carbohydrate antigen 19-9 (CA199) were examined. Resting electrocardiogram (ECG) of 5-min was collected prior to surgical treatments to enable the HRV analysis. Twelve nonlinear HRV indices covering the irregularity, complexity, asymmetry, and temporal correlation of heartbeat fluctuations were obtained. Increased short-range temporal correlations, decreased asymmetry, and increased irregularity of heartbeat fluctuations were associated with higher FIB level. Increased irregularity and decreased complexity were also associated with higher CEA level. These associations were independent of age, sex, BMI, alcohol consumption, history of diabetes, left ventricular ejection fraction, and anemia. The results support the hypothesis that perturbations in nonlinear dynamical patterns of HRV predict increased GC severity. Replication in larger samples as well as the examination of longitudinal associations of HRV nonlinear features with cancer prognosis/survival are warranted.