Cardiac state diagnosis using higher order spectra of heart rate variability

Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart, by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computer-based intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are nonlinear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of nonlinear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and seven classes of arrhythmia. We present some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. We also extracted features from the HOS and performed an analysis of variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test.

Investigation on Heart Rate Variability (HRV) and psycho-social-affective adjustment in Italian women with ovarian cancer

INTRODUZIONE: L’integrazione mente-corpo applicata ad un ambito patologico predominante in questi tempi, come il cancro, è il nucleo di questa tesi. Il background teorico entro cui è inserita, è quello della Psiconeuroendocrinoimmunologia (Bottaccioli, 1995) e Psico-Oncologia. Sono state identificate, nella letteratura scientifica, le connessioni tra stati psicologici (mente) e condizioni fisiologiche (corpo). Le variabili emerse come potenzialmente protettive in pazienti che si trovano ad affrontare il cancro sono: il supporto sociale, l’immagine corporea, il coping e la Qualità della Vita, insieme all’indice fisiologico Heart Rate Variability (HRV; Shaffer & Venner, 2013). Il potenziale meccanismo della connessione tra queste variabili potrebbe essere spiegato dall’azione del Nervo Vago, come esposto nella Teoria Polivagale di Stephen Porges (2007; 2009). OBIETTIVI: Gli obiettivi principali di questo studio sono: 1. Valutare l’adattamento psicologico alla patologia in termini di supporto sociale percepito, immagine corporea, coping prevalente e qualità della vita in donne con cancro ovarico; 2. Valutare i valori di base HRV in queste donne; 3. Osservare se livelli più elevati di HRV sono associati ad un migliore adattamento psicologico alla patologia; 4. Osservare se una peggiore percezione dell’immagine corporea e l’utilizzo di strategie di coping disadattive sono associate ad una Qualità della Vita più scarsa. METODO: 38 donne affette da cancro ovarico, al momento della valutazione libere da patologia, sono state reclutate presso la clinica oncologica del reparto di Ginecologia dell’Azienda Ospedaliero-Universitaria di Parma, Italia. Ad ogni partecipante è stato chiesto di compilare una batteria di test composta da: MSPSS, per la valutazione del supporto sociale percepito; DAS-59, per la valutazione dell’immagine corporea; MAC, per la valutazione delle strategie di coping prevalenti utilizzate verso il cancro; EORTC-QLQ30, per la valutazione della Qualità della Vita. Per ogni partecipante è stato registrato HRV di base utilizzando lo strumento emWave (HeartMath). RISULTATI PRINCIPALI: Rispondendo agli obiettivi 1 e 2, in queste donne si è rilevato una alto tasso di supporto sociale percepito, in particolare ricevuto dalla persona di riferimento. L’area rivelatasi più critica nel supporto sociale è quella degli amici. Per quanto riguarda l’immagine corporea, la porzione di campione dai 30 ai 61 anni, ha delle preoccupazioni globali legate all’immagine corporea paragonabili ai dati provenienti dalla popolazione generale con preoccupazioni riguardo l’aspetto corporeo. Invece, nella porzione di campione dai 61 anni in su, il pattern di disagio verso l’aspetto fisico sembra decisamente peggiorare. Inoltre, in questo campione, si è rilevato un disagio globale verso l’immagine corporea significativamente più alto rispetto ai valori normativi presenti in letteratura riferiti a donne con cancro al seno con o senza mastectomia (rispettivamente t(94)= -4.78; p<0.000001; t(110)= -6.81;p<0.000001). La strategia di coping più utilizzata da queste donne è lo spirito combattivo, seguito dal fatalismo. Questo campione riporta, inoltre, una Qualità della Vita complessivamente soddisfacente, con un buon livello di funzionamento sociale. L’area di funzionalità più critica risulta essere il funzionamento emotivo. Considerando i sintomi prevalenti, i più riferiti sono affaticamento, disturbi del sonno e dolore. Per definire, invece, il pattern HRV, sono stati confrontati i dati del campione con quelli presenti in letteratura, riguardanti donne con cancro ovarico. Il campione valutato in questo studio, ha un HRV SDNN (Me=28.2ms) significativamente più alto dell’altro gruppo. Tuttavia, confrontando il valore medio di questo campione con i dati normativi sulla popolazione sana (Me=50ms), i nostri valori risultano drasticamente più bassi. In ultimo, donne che hanno ricevuto diagnosi di cancro ovarico in età fertile, sembrano avere maggiore HRV, migliore funzionamento emotivo e minore sintomatologia rispetto alle donne che hanno ricevuto diagnosi non in età fertile. Focalizzando l’attenzione sulla ricerca di relazioni significative tra le variabili in esame (obiettivo 3 e 4) sono state trovate numerose correlazioni significative tra: l’età e HRV, supporto percepito , Qualità della Vita; Qualità della Vita e immagine corporea, supporto sociale, strategie di coping; strategie di coping e immagine corporea, supporto sociale; immagine corporea e supporto sociale; HRV e supporto sociale, Qualità della Vita. Per verificare la possibile connessione causale tra le variabili considerate, sono state applicate regressioni lineari semplici e multiple per verificare la bontà del modello teorico. Si è rilevato che HRV è significativamente positivamente influenzata dal supporto percepito dalla figura di riferimento, dal funzionamento di ruolo, dall’immagine corporea totale. Invece risulta negativamente influenzata dal supporto percepito dagli amici e dall’uso di strategie di coping evitanti . La qualità della vita è positivamente influenzata da: l’immagine corporea globale e l’utilizzo del fatalismo come strategia di coping prevalente. Il funzionamento emotivo è influenzato dal supporto percepito dalla figura di riferimento e dal fatalismo. DISCUSSIONI E CONCLUSIONI: Il campione Italiano valutato, sembra essere a metà strada nell’adattamento dello stato psicologico e dell’equilibrio neurovegetativo al cancro. Sicuramente queste donne vivono una vita accettabile, in quanto sopravvissute al cancro, ma sembra anche che portino con sé preoccupazioni e difficoltà, in particolare legate all’accettazione della loro condizione di sopravvissute. Infatti, il migliore adattamento si riscontra nelle donne che hanno avuto peggiori condizioni in partenza: stadio del cancro avanzato, più giovani, con diagnosi ricevuta in età fertile. Pertanto, è possibile suggerire che queste condizioni critiche forzino queste donne ad affrontare apertamente il cancro e la loro situazione di sopravvissute al cancro, portandole ad “andare avanti” piuttosto che “tornare indietro”. Facendo riferimento alle connessioni tra variabili psicologiche e fisiologiche in queste donne, si è evidenziato che HRV è influenzata dalla presenza di figure significative ma, in particolare, è presumibile che sia influenzata da un’appropriata condivisione emotiva con queste figure. Si è anche evidenziato che poter continuare ad essere efficaci nel proprio contesto personale si riflette in un maggiore HRV, probabilmente in quanto permette di preservare il senso di sé, riducendo in questo modo lo stress derivante dall’esperienza cancro. Pertanto, HRV in queste donne risulta associato con un migliore adattamento psicologico. Inoltre, si è evidenziato che in queste donne la Qualità della Vita è profondamente influenzata dalla percezione dell’immagine corporea. Si tratta di un aspetto innovativo che è stato rilevato in questo campione e che, invece, nei precedenti studi non è stato indagato. In ultimo, la strategia di coping fatalismo sembra essere protettiva e sembra facilitare il processo di accettazione del cancro. Si spera sinceramente che le ricerche future possano superare i limiti del presente studio, come la scarsa numerosità e l’uso di strumenti di valutazione che, per alcuni aspetti come la scala Evitamento nel MAC, non centrano totalmente il target di indagine. Le traiettorie future di questo studio sono: aumentare il numero di osservazioni, reclutando donne in diversi centri specialistici in diverse zone d’Italia; utilizzare strumenti più specifici per valutare i costrutti in esame; valutare se un intervento di supporto centrato sul miglioramento di HRV (come HRV Biofeedback) può avere una ricaduta positiva sull’adattamento emotivo e la Qualità della Vita.

Analysis of cardiac and epileptic signals using higher order spectra

The theory of nonlinear dyamic systems provides some new methods to handle complex systems. Chaos theory offers new concepts, algorithms and methods for processing, enhancing and analyzing the measured signals. In recent years, researchers are applying the concepts from this theory to bio-signal analysis. In this work, the complex dynamics of the bio-signals such as electrocardiogram (ECG) and electroencephalogram (EEG) are analyzed using the tools of nonlinear systems theory. In the modern industrialized countries every year several hundred thousands of people die due to sudden cardiac death. The Electrocardiogram (ECG) is an important biosignal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computerbased intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and four classes of arrhythmia. This thesis presents some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. Several features were extracted from the HOS and subjected an Analysis of Variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, seven features were extracted from the heart rate signals using HOS and fed to a support vector machine (SVM) for classification. The performance evaluation protocol in this thesis uses 330 subjects consisting of five different kinds of cardiac disease conditions. The classifier achieved a sensitivity of 90% and a specificity of 89%. This system is ready to run on larger data sets. In EEG analysis, the search for hidden information for identification of seizures has a long history. Epilepsy is a pathological condition characterized by spontaneous and unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic early detection of the seizure onsets would help the patients and observers to take appropriate precautions. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, these features are used to train both a Gaussian mixture model (GMM) classifier and a Support Vector Machine (SVM) classifier. Results show that the classifiers were able to achieve 93.11% and 92.67% classification accuracy, respectively, with selected HOS based features. About 2 hours of EEG recordings from 10 patients were used in this study. This thesis introduces unique bispectrum and bicoherence plots for various cardiac conditions and for normal, background and epileptic EEG signals. These plots reveal distinct patterns. The patterns are useful for visual interpretation by those without a deep understanding of spectral analysis such as medical practitioners. It includes original contributions in extracting features from HRV and EEG signals using HOS and entropy, in analyzing the statistical properties of such features on real data and in automated classification using these features with GMM and SVM classifiers.

Cardiac health diagnosis using higher order spectra and support vector machine

The Electrocardiogram (ECG) is an important bio-signal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. The HRV signal can be used as a base signal to observe the heart's functioning. These signals are non-linear and non-stationary in nature. So, higher order spectral (HOS) analysis, which is more suitable for non-linear systems and is robust to noise, was used. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, we have extracted seven features from the heart rate signals using HOS and fed them to a support vector machine (SVM) for classification. Our performance evaluation protocol uses 330 subjects consisting of five different kinds of cardiac disease conditions. We demonstrate a sensitivity of 90% for the classifier with a specificity of 87.93%. Our system is ready to run on larger data sets.

Higher order spectra based support vector machine for arrhythmia classification

Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. HRV analysis is an important tool to observe the heart’s ability to respond to normal regulatory impulses that affect its rhythm. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. A computer-based arrhythmia detection system of cardiac states is very useful in diagnostics and disease management. In this work, we studied the identification of the HRV signals using features derived from HOS. These features were fed to the support vector machine (SVM) for classification. Our proposed system can classify the normal and other four classes of arrhythmia with an average accuracy of more than 85%.

Evidence for a respiratory component, similar to mammalian respiratory sinus arrhythmia, in the heart rate variability signal from the rattlesnake, Crotalus durissus terrificus

Autonomic control of heart rate variability and the central location of vagal preganglionic neurones (VPN) were examined in the rattlesnake ( Crotalus durissus terrificus), in order to determine whether respiratory sinus arrhythmia (RSA) occurred in a similar manner to that described for mammals. Resting ECG signals were recorded in undisturbed snakes using miniature datalogging devices, and the presence of oscillations in heart rate (f(H)) was assessed by power spectral analysis (PSA). This mathematical technique provides a graphical output that enables the estimation of cardiac autonomic control by measuring periodic changes in the heart beat interval. At fH above 19 min(-1) spectra were mainly characterised by low frequency components, reflecting mainly adrenergic tonus on the heart. By contrast, at f(H) below 19 min(-1) spectra typically contained high frequency components, demonstrated to be cholinergic in origin. Snakes with a f(H) > 19 min(-1) may therefore have insufficient cholinergic tonus and/or too high an adrenergic tonus acting upon the heart for respiratory sinus arrhythmia ( RSA) to develop. A parallel study monitored f(Hd) simultaneously with the intraperitoneal pressures associated with lung inflation. Snakes with a fH < 19 min(-1) exhibited a high frequency (HF) peak in the power spectrum, which correlated with ventilation rate (f(V)). Adrenergic blockade by propranolol infusion increased the variability of the ventilation cycle, and the oscillatory component of the f(H) spectrum broadened accordingly. Infusion of atropine to effect cholinergic blockade abolished this HF component, confirming a role for vagal control of the heart in matching f(H) and f(V) in the rattlesnake. A neuroanatomical study of the brainstem revealed two locations for vagal preganglionic neurones (VPN). This is consistent with the suggestion that generation of ventilatory components in the heart rate variability (HRV) signal are dependent on spatially distinct loci for cardiac VPN. Therefore, this study has demonstrated the presence of RSA in the HRV signal and a dual location for VPN in the rattlesnake. We suggest there to be a causal relationship between these two observations.

The effect of post-exercise hydrotherapy on subsequent exercise performance and heart rate variability

We investigated the effect of hydrotherapy on time-trial performance and cardiac parasympathetic reactivation during recovery from intense training. On three occasions, 18 well-trained cyclists completed 60 min high-intensity cycling, followed 20 min later by one of three 10-min recovery interventions: passive rest (PAS), cold water immersion (CWI), or contrast water immersion (CWT). The cyclists then rested quietly for 160 min with R-R intervals and perceptions of recovery recorded every 30 min. Cardiac parasympathetic activity was evaluated using the natural logarithm of the square root of mean squared differences of successive R-R intervals (ln rMSSD). Finally, the cyclists completed a work-based cycling time trial. Effects were examined using magnitude-based inferences. Differences in time-trial performance between the three trials were trivial. Compared with PAS, general fatigue was very likely lower for CWI (difference [90% confidence limits; -12% (-18; -5)]) and CWT [-11% (-19; -2)]. Leg soreness was almost certainly lower following CWI [-22% (-30; -14)] and CWT [-27% (-37; -15)]. The change in mean ln rMSSD following the recovery interventions (ln rMSSD(Post-interv)) was almost certainly higher following CWI [16.0% (10.4; 23.2)] and very likely higher following CWT [12.5% (5.5; 20.0)] compared with PAS, and possibly higher following CWI [3.7% (-0.9; 8.4)] compared with CWT. The correlations between performance, ln rMSSD(Post-interv) and perceptions of recovery were unclear. A moderate correlation was observed between ln rMSSD(Post-interv) and leg soreness [r = -0.50 (-0.66; -0.29)]. Although the effects of CWI and CWT on performance were trivial, the beneficial effects on perceptions of recovery support the use of these recovery strategies.

Vagal control of heart rate and cardiac shunts in reptiles: Relation to metabolic state

The vagus is clearly of primary importance in the regulation of reptilian cardiorespiratory systems. Vagal control of pulmonary blood flow and cardiac shunts provides reptiles with an additional means of regulating arterial oxygen levels that is not present in endothermic vertebrates (birds and mammals). Within a given species, there exists a clear correlation between withdrawal of vagal tone on the cardiovascular system and elevated metabolic rate. Undisturbed and resting reptiles are normally characterised by high vagal tone, low pulmonary blood flow and large right-left (R-L) cardiac shunts. The low oxygen levels that result from the large R-L shunt may serve to regulate metabolism. However, when metabolism is increased by temperature, exercise or digestion, the R-L cardiac shunt is reduced, which serves to increase oxygen delivery. This response is partially elicit ed by reduction of vagal tone. Interspecies comparisons reveal a similar pattern. Thus, species that are able to sustain the highest metabolic rates possess the highest degree of anatomical ventricular separation and, therefore, less cardiac shunting. It is interesting to note that when cardiac shunts occur in mammals, due for example to developmental defects, they are associated with reduced maximal metabolic rates and impaired exercise tolerance. It appears, therefore, that full separation of ventricular blood flows was a prerequisite for the evolution of high aerobic metabolic rates and exercise stamina in mammals and birds.

Effects of Cold Water Immersion and Active Recovery on Post-Exercise Heart Rate Variability

The aim of the present study was to investigate the potential benefits of cold water immersion (CWI) and active recovery (AR) on blood lactate concentration ([Lac]) and heart rate variability (HRV) indices following high-intensity exercise. 20 male subjects were recruited. on the first visit, an incremental test was performed to determine maximal oxygen consumption and the associated speed (MAS). The remaining 3 visits for the performance of constant velocity exhaustive tests at MAS and different recovery methods (6 min) were separated by 7-day intervals [randomized: CWI, AR or passive recovery (PR)]. The CWI and AR lowered [Lac] (p < 0.05) at 11, 13 and 15 min after exercise cessation in comparison to PR. There was a 'time' and 'recovery mode' interaction for 2 HRV indices: standard deviation of normal R-R intervals (SDNN) (partial eta squared = 0.114) and natural log of low-frequency power density (lnLF) (partial eta squared = 0.090). CWI presented significantly higher SDNN compared to PR at 15 min of recovery (p < 0.05). In addition, greater SDNN values were found in CWI vs. AR during the application of recovery interventions, and at 30 and 75 min post-exercise (p < 0.05 for all differences). The lnLF during the recovery interventions and at 75 min post-exercise was greater using CWI compared with AR (p < 0.05). For square root of the mean of the sum of the squares of differences between adjacent R-R intervals (RMSSD) and natural log of high-frequency power density (lnHF), a moderate effect size was found between CWI and PR during the recovery interventions and at 15 min post-exercise. Our findings show that AR and CWI offer benefits regarding the removal of [Lac] following high-intensity exercise. While limited, CWI results in some improvement in post-exercise cardiac autonomic regulation compared to AR and PR. Further, AR is not recommended if the aim is to accelerate the parasympathetic reactivation.

Chronic obstructive pulmonary disease and heart rate variability: a literature update

Background: The literature indicates that chronic obstructive pulmonary disease (COPD) affects cardiac autonomic control. In this study, we conducted a literature review in order to investigate the heart rate variability (HRV) in COPD subjects. Methods: A search was performed in Medline database, using the link between the keywords: “autonomic nervous system”, “cardiovascular system”, “COPD” and “heart rate variability”. Results: The search resulted in a total of 40 references. Amongst these references, the first exclusion resulted in the barring of 29 titles and abstracts, which were not clearly related to the purpose of review. This resulted in a total of 11 articles that were then read and utilized in the review. The selected studies indicated that there is significant reduction of HRV in patients with COPD, characterized by reduction of indices that assess parasympathetic activity in addition to dealing with the global autonomic modulation. We also established that supervised exercise can reduce these harmful effects in COPD patients. Also, it was reported that the use of non-invasive ventilation in these patients may contribute to the improvement of respiratory symptoms, with no impairing, and may even induce positive responses in cardiac autonomic regulation. Conclusion: The studies indicate a need for further investigations to guide future therapies to improve the treatment of cardiovascular system in the respiratory diseases.

Wavelet analysis of heart rate variability related to nocturnal frontal lobe epilepsy seizures

Introduction: Nocturnal frontal lobe epilepsy (NFLE) is a distinct syndrome of partial epilepsy whose clinical features comprise a spectrum of paroxysmal motor manifestations of variable duration and complexity, arising from sleep. Cardiovascular changes during NFLE seizures have previously been observed, however the extent of these modifications and their relationship with seizure onset has not been analyzed in detail. Objective: Aim of present study is to evaluate NFLE seizure related changes in heart rate (HR) and in sympathetic/parasympathetic balance through wavelet analysis of HR variability (HRV). Methods: We evaluated the whole night digitally recorded video-polysomnography (VPSG) of 9 patients diagnosed with NFLE with no history of cardiac disorders and normal cardiac examinations. Events with features of NFLE seizures were selected independently by three examiners and included in the study only if a consensus was reached. Heart rate was evaluated by measuring the interval between two consecutive R-waves of QRS complexes (RRi). RRi series were digitally calculated for a period of 20 minutes, including the seizures and resampled at 10 Hz using cubic spline interpolation. A multiresolution analysis was performed (Daubechies-16 form), and the squared level specific amplitude coefficients were summed across appropriate decomposition levels in order to compute total band powers in bands of interest (LF: 0.039062 - 0.156248, HF: 0.156248 - 0.624992). A general linear model was then applied to estimate changes in RRi, LF and HF powers during three different period (Basal) (30 sec, at least 30 sec before seizure onset, during which no movements occurred and autonomic conditions resulted stationary); pre-seizure period (preSP) (10 sec preceding seizure onset) and seizure period (SP) corresponding to the clinical manifestations. For one of the patients (patient 9) three seizures associated with ictal asystole were recorded, hence he was treated separately. Results: Group analysis performed on 8 patients (41 seizures) showed that RRi remained unchanged during the preSP, while a significant tachycardia was observed in the SP. A significant increase in the LF component was instead observed during both the preSP and the SP (p<0.001) while HF component decreased only in the SP (p<0.001). For patient 9 during the preSP and in the first part of SP a significant tachycardia was observed associated with an increased sympathetic activity (increased LF absolute values and LF%). In the second part of the SP a progressive decrease in HR that gradually exceeded basal values occurred before IA. Bradycardia was associated with an increase in parasympathetic activity (increased HF absolute values and HF%) contrasted by a further increase in LF until the occurrence of IA. Conclusions: These data suggest that changes in autonomic balance toward a sympathetic prevalence always preceded clinical seizure onset in NFLE, even when HR changes were not yet evident, confirming that wavelet analysis is a sensitive technique to detect sudden variations of autonomic balance occurring during transient phenomena. Finally we demonstrated that epileptic asystole is associated with a parasympathetic hypertonus counteracted by a marked sympathetic activation.

Symbolic Dynamics Analysis: a new methodology for foetal heart rate variability analysis

Cardiotocography (CTG) is a widespread foetal diagnostic methods. However, it lacks of objectivity and reproducibility since its dependence on observer's expertise. To overcome these limitations, more objective methods for CTG interpretation have been proposed. In particular, many developed techniques aim to assess the foetal heart rate variability (FHRV). Among them, some methodologies from nonlinear systems theory have been applied to the study of FHRV. All the techniques have proved to be helpful in specific cases. Nevertheless, none of them is more reliable than the others. Therefore, an in-depth study is necessary. The aim of this work is to deepen the FHRV analysis through the Symbolic Dynamics Analysis (SDA), a nonlinear technique already successfully employed for HRV analysis. Thanks to its simplicity of interpretation, it could be a useful tool for clinicians. We performed a literature study involving about 200 references on HRV and FHRV analysis; approximately 100 works were focused on non-linear techniques. Then, in order to compare linear and non-linear methods, we carried out a multiparametric study. 580 antepartum recordings of healthy fetuses were examined. Signals were processed using an updated software for CTG analysis and a new developed software for generating simulated CTG traces. Finally, statistical tests and regression analyses were carried out for estimating relationships among extracted indexes and other clinical information. Results confirm that none of the employed techniques is more reliable than the others. Moreover, in agreement with the literature, each analysis should take into account two relevant parameters, the foetal status and the week of gestation. Regarding the SDA, results show its promising capabilities in FHRV analysis. It allows recognizing foetal status, gestation week and global variability of FHR signals, even better than other methods. Nevertheless, further studies, which should involve even pathological cases, are necessary to establish its reliability.

Sex differences in heart rate variability: a longitudinal study in international elite cross-country skiers

PURPOSE: Exercise-related sudden cardiac deaths (SCD) occur with a striking male predominance. A higher sympathetic tone in men has been suggested as risk factor for SCD. Elite athletes have the highest risk for exercise-related SCD. We aimed to analyze the autonomic nervous system of elite cross-country skiers from Norway, Russia and Switzerland in supine position and after orthostatic challenge in various training periods (TP). METHOD: Measurements of heart rate variability (HRV) were performed on a weekly basis over 1 year using an orthostatic challenge test with controlled breathing. Main outcome parameters were the high-frequency power in supine position (HFsupine) as marker of cardiac parasympathetic activity and the low-frequency/high-frequency power ratio after orthostatic challenge (LF/HFstand) as marker of cardiac sympathetic activation. Training intensity and duration were recorded daily and expressed as training strain. The training year was divided into three TPs. An average of weekly HRV measurements was calculated for each TP. RESULT: Female (n = 19, VO2max 62.0 +/- 4.6 ml kg(-1) min(-1), age 25.8 +/- 4.3 years) and male (n = 16, VO2max 74.3 +/- 6.3 ml kg(-1) min(-1), age 24.4 +/- 4.2 years) athletes were included. Training strain was comparable between sexes (all p > 0.05) and changed between TPs (all p < 0.05) while no HRV parameters changed over time. There were no sex differences in HFsupine while the LF/HFstand was significantly higher in male athletes in all TPs. CONCLUSION: For a comparable amount of training, male athletes showed constantly higher markers of sympathetic activity after a provocation maneuver. This may explain part of the male predominance in sports-related SCD.

Impact of artifact correction methods on R-R interbeat signals to quantifying heart rate variability (HRV) according to linear and nonlinear methods.

In the analysis of heart rate variability (HRV) are used temporal series that contains the distances between successive heartbeats in order to assess autonomic regulation of the cardiovascular system. These series are obtained from the electrocardiogram (ECG) signal analysis, which can be affected by different types of artifacts leading to incorrect interpretations in the analysis of the HRV signals. Classic approach to deal with these artifacts implies the use of correction methods, some of them based on interpolation, substitution or statistical techniques. However, there are few studies that shows the accuracy and performance of these correction methods on real HRV signals. This study aims to determine the performance of some linear and non-linear correction methods on HRV signals with induced artefacts by quantification of its linear and nonlinear HRV parameters. As part of the methodology, ECG signals of rats measured using the technique of telemetry were used to generate real heart rate variability signals without any error. In these series were simulated missing points (beats) in different quantities in order to emulate a real experimental situation as accurately as possible. In order to compare recovering efficiency, deletion (DEL), linear interpolation (LI), cubic spline interpolation (CI), moving average window (MAW) and nonlinear predictive interpolation (NPI) were used as correction methods for the series with induced artifacts. The accuracy of each correction method was known through the results obtained after the measurement of the mean value of the series (AVNN), standard deviation (SDNN), root mean square error of the differences between successive heartbeats (RMSSD), Lomb\'s periodogram (LSP), Detrended Fluctuation Analysis (DFA), multiscale entropy (MSE) and symbolic dynamics (SD) on each HRV signal with and without artifacts. The results show that, at low levels of missing points the performance of all correction techniques are very similar with very close values for each HRV parameter. However, at higher levels of losses only the NPI method allows to obtain HRV parameters with low error values and low quantity of significant differences in comparison to the values calculated for the same signals without the presence of missing points.

Changes in heart rate variability associated with moderate alcohol consumption

Technological advances have driven some attempt of vital parameters monitoring in adverse environments; these improvements will make possible to monitor cardiac activity also in automotive environments. In this scenario, heart rate changes associated with alcohol consumption, become of great importance to assess the drivers state during time. This paper presents the results of a first set of experiments aimed to discover heart rate variability modification induced by moderate assumption of alcoholic drink (i.e. single draft beer) as that typically occurs in weekend among some people. In the study, twenty subjects were enrolled and for each of them two electrocardiographic recordings were carried out: the first before alcohol ingestion and the second after 25-30 minutes. Each participant remained fasting until the second ECG acquisition was completed. ECG signal were analyzed by typical timedomain, frequency and non linear analysis. Results showed a small increase in LF/HF ratio which reflects a dominance of the sympathetic system over the parasympathetic system, and an increase in signal complexity as proven by non linear analysis. However, the study highlighted the need to monitor HRV starting from alcohol ingestion until its complete metabolization to allow a more precise description of its variation. © Springer International Publishing Switzerland 2014.