HRV

The following paper reviews work on non-contact measurement of human physiological parameter, more specifically measurement of the human heart rate (HR) and consequently the heart rate variability (HRV), which is regarded to be an important indicator of autonomic nervous system activity proven to be prognostic of the likelihood of future health related events. The HRV analysis is simple and low cost method for obtaining the activities of cardiac system and in turn activities of Autonomic Nervous System (ANS). The HRV analysis is carried out mainly through linear methods and nonlinear method. The linear methods are broadly classified in to time domain method and frequency domain methods. Since, the cardiac activity is complex and a quasi-periodic nonlinear result provides more pragmatic results. The nonlinear includes measures like Detrended Fluctuation Analysis (DFA), Poincare plot and correlation analysis. There are many builtin softwares available for HRV analysis namely POLYYAN, KARDIA, RHRV, ARTiiFACT, aHRV, gHRV, HRV tool in Labview, Kubios Software etc. Among them Kubios, aHRV, gHRV are open source software, easily accessible and user friendly. The software provides the advantages of obtaining the HRV parameters with ease and reliability. In various studies HRV has been studied with conditions like myocardial infarction, blood pressure, neurological ailments, renal failure, effects of drugs, in addictions like alcohol and smoking, sleeping stages, influence of age and gender on HRV. The ability to quantify the cardiac activity in a non-contact method could prove to become an essential alternative to the conventional methods in the clinical field as well as in the more industrially oriented fields. Some of the published work so far shows that the measurement of cardiac activity in a non-contact manner is undeniably possible and in some cases also very accurate, however there are several drawbacks to the methods which need to be taken into account when performing the measurements. The following paper includes a brief description of  HRV, its relation to ANS, the studies carried out for analyzing HRV in various diseased conditions. The methods used for analyzing HRV, linear and nonlinear methods, challenges and drawbacks in measuring HRV and brief description of the two usual methods, electrocardiogram (ECG) and photo plethysmography (PPG), and later on focuses on methods of non-contact measuring of HRV with webcam and smart phone cameras. Our study represents a comparative review of these methods with the conventional methods while emphasizing their advantages and disadvantages.

Keywords- HRV(Heart Rate Variability), ANS(Autonomic Nervous System), ECG(Electrocardiogram), Webcam, Smartphone.

Analysis of heart rate variability (HRV) is a valuable, non-invasive method for quantifying autonomic cardiac control in humans. Frequency-domain analysis of HRV involving myocardial ischaemic episodes should take into account its non-stationary behaviour. The wavelet transform is an alternative tool for the analysis of non-stationary signals. Fourteen patients have been analysed, ranging from 40 to 64 years old and selected from the European Electrocardiographic ST-T Database (ESDB).

Abstract Heart rate variability (HRV) is an easily measurable physiological indicator with relevant clinical applicability. One important problem for HRV researchers is the lack of common data collections that could be used for testing their own algorithms. Moreover, free software tools for analyzing ECG records are scarce or they do not exist. Inspired by the PhysioNet Website (http://www. physionet. org), we have developed a Web portal, HRV-Site, located at http://www. hrv-site. net, and devoted to the HRV.

This systematic review evaluates and summarizes the evidence of the association between psychosocial work environment as indicated by several work-stress models such as Job-Demand-Control (JDC), Effort-Reward-Imbalance (ERI), or Organizational Justice (OJ) and autonomic nervous system (ANS) function as indexed by heart rate variability (HRV). We conducted a systematic literature search following the PRISMA-Statement in eleven databases including Medline, Web of Science and PsycINFO to address medical as well as psychological aspects of the relation between psychosocial work-stress models and HRV. We identified 19 publications with a total of 8382 employees from ten countries reporting data from the years 1976-2008. Overall, nine of all studies report a negative and significant association between vagally-mediated HRV and measures of stress at work, while eight of all studies report a negative and significant association to mixed sympathetic and parasympathetic measures of HRV. This systematic review provides evidence that adverse psychosocial work conditions are negatively associated with ANS function as indexed by HRV.

Background: Hyperthyroidism is associated with altered cardiac autonomic nervous activity (CANA). Heart Rate Variability (HRV) analysis is a promising technique to quantify CANA and therefore can be done in hyperthyroidism. Objective: To observe the HRV parameters in patients with hyperthyroidism to find out the influence of excess thyroid hormone on cardiac autonomic nervous activities. Method: The cross sectional study was carried out on 60 hyperthyroid patients (groupB) aged 30-50 years in the Department of Physiology, BSMMU, Dhaka from 1st July 2007 to 30th June 2008. Age and sex matched 20 apparently healthy euthyroids were also studied for comparison (group A). On the basis of treatment, they were further divided into group B1 consisting of 30 untreated newly diagnosed patients and group B2 consisting of 30 hyperthyroid patients treated with antithyroid drugs for at least 2 months. The patients were selected from the Out Patient Department of Endocrinology, BSMMU, Dhaka. To as...

Purpose: The identification of subjects with systemic sarcoidosis at higher risk for sudden death is an unresolved issue. An influence of the autonomic activity on the genesis of ventricular arrhythmias was postulated. Heart rate variability (HRV) analysis provides a useful method to measure autonomic activity, and is a predictor of increased risk of death in various conditions. Therefore, the aim of the study was to evaluate HRV in patients with systemic sarcoidosis.Methods: The study included 35 patients with biopsy proven systemic sarcoidosis who were not taking antiarrhythmic medications. Thallium scintigraphy was performed to all patients with systemic sarcoidosis. The cardiac sarcoidosis was accepted in 16 patients as abnormal thallium scintigraphy and normal coronary arteriography. The time-domain analysis of HRV was expressed as the standard deviation of all normal to normal NN intervals (SDNN) detected during 24-hour Holter monitoring. Twenty-four healthy subjects represented a control group for HRV analysis.Results: There were no differences in age (44 ± 13 years for cardiac sarcoidosis, 42 ± 15 years for noncardiac sarcoidosis, and 40 ± 10 years for control group; P = NS), sex (the ratio of female; 63%, 68%, and 55%, respectively; P = NS), and echocardiographic ejection fraction (63 ± 10%, 67 ± 8%, and 69 ± 6%, respectively; P = NS) among study groups. The mean SDNN value of the group with cardiac sarcoidosis was significantly lower than both the group with noncardiac sarcoidosis and the control group (72 ± 32 ms vs 110 ± 46 ms and 152 ± 36 ms; P < 0.05, respectively).Conclusion: HRV is decreased in patients with systemic sarcoidosis compared to the control group. This decreasing is more obvious in patients with cardiac sarcoidosis.

The central autonomic network (CAN) has been described in animal models but has been difficult to elucidate in humans. Potential confounds include physiological noise artifacts affecting brainstem neuroimaging data, and difficulty in deriving non-invasive continuous assessments of autonomic modulation. We have developed and implemented a new method which relates cardiac-gated fMRI timeseries with continuous-time heart rate variability (HRV) to estimate central autonomic processing. As many autonomic structures of interest are in brain regions strongly affected by cardiogenic pulsatility, we chose to cardiac-gate our fMRI acquisition to increase sensitivity. Cardiac-gating introduces T1-variability, which was corrected by transforming fMRI data to a fixed TR using a previously published method [Guimaraes, A.R., Melcher, J.R., et al., 1998. Imaging subcortical auditory activity in humans. Hum. Brain Mapp. 6(1), 33–41]. The electrocardiogram was analyzed with a novel point process adaptive-filter algorithm for computation of the high-frequency (HF) index, reflecting the time-varying dynamics of efferent cardiovagal modulation. Central command of cardiovagal outflow was inferred by using the resample HF timeseries as a regressor to the fMRI data. A grip task was used to perturb the autonomic nervous system. Our combined HRV-fMRI approach demonstrated HF correlation with fMRI activity in the hypothalamus, cerebellum, parabrachial nucleus/locus ceruleus, periaqueductal gray, amygdala, hippocampus, thalamus, and dorsomedial/dorsolateral prefrontal, posterior insular, and middle temporal cortices. While some regions consistent with central cardiovagal control in animal models gave corroborative evidence for our methodology, other mostly higher cortical or limbic-related brain regions may be unique to humans. Our approach should be optimized and applied to study the human brain correlates of autonomic modulation for various stimuli in both physiological and pathological states.

Abstract: The heart rate variability (HRV) analysis has been proven to be an effective tool for the diagnosis of several diseases, such as heart failure or diabetes. To measure the HRV, various algorithms have been developed employing different programming languages. In this paper, we present a new package for R, a free software environment for statistical computing and graphics. This package, called R-HRV, offers functions for performing power spectral analysis of heart rate data.

Background: Extensive research has been done to demystify the effects of sleep deprivation on cognitive functions, memory, and reasoning ability. However, there is a lacuna in regard to the effects on autonomic function and perceived stress as well as its modulation through yogic relaxation. Healthcare professionals often work at night, and the effect of acute overnight sleep deprivation on their performance is crucial. Aims and Objectives: The present study was undertaken to study the effects of overnight sleep deprivation on autonomic function and perceived stress in health-care professionals and to determine its modulation through yogic relaxation (Shavasana). Materials and Methods: A total of 35 healthcare professionals, aged between 20 and 25 years, were recruited from emergency services wing (casualty) of MGMC and RI, Puducherry, and taught yogic relaxation. Heart rate (HR), blood pressure (BP), and HR variability (HRV) were recorded and Cohen's perceived stress scale (PSS) administered before the commencement of day duty. Parameters were again recorded after overnight sleep deprivation due to night shift work and then after they practiced yogic relaxation (Shavasana). As data passed normality testing, Student's paired t-test was used to compare the changes after sleep deprivation and then after yogic relaxation. Results: Overnight sleep deprivation resulted in statistically significant (P < 0.05) increases in systolic BP (SBP), low frequency (LF), LF/high frequency (HF), diastolic BP (DBP), PSS, and mean HR. This was coupled with significant decreases in mean RR, SDNN, pNN50, HF, and RMSSD. Following yogic relaxation, these changes were reversed, and significant decreases were witnessed in LF, LF/ HF, SBP, mean HR, DBP, and PSS with significant increases in mean RR, pNN50, HF, RMSSD, and SDNN. Conclusion: The findings of our study reiterate the negative effects of sleep deprivation on cardiac autonomic status. Such deleterious effects may be partially reversed by practicing yogic relaxation (Shavasana). Such conscious relaxation may be able to help correct imbalance of autonomic nervous system by enhancing parasympathetic tone and reducing sympathetic overactivity.

Background: Extensive research has been done to demystify the effects of sleep deprivation on cognitive functions, memory, and reasoning ability. However, there is a lacuna in regard to the effects on autonomic function and perceived stress as well as its modulation through yogic relaxation. Healthcare professionals often work at night, and the effect of acute overnight sleep deprivation on their performance is crucial. Aims and Objectives: The present study was undertaken to study the effects of overnight sleep deprivation on autonomic function and perceived stress in health-care professionals and to determine its modulation through yogic relaxation (Shavasana). Materials and Methods: A total of 35 healthcare professionals, aged between 20 and 25 years, were recruited from emergency services wing (casualty) of MGMC and RI, Puducherry, and taught yogic relaxation. Heart rate (HR), blood pressure (BP), and HR variability (HRV) were recorded and Cohen’s perceived stress scale (PSS) administered before the commencement of day duty. Parameters were again recorded after overnight sleep deprivation due to night shift work and then after they practiced yogic relaxation (Shavasana). As data passed normality testing, Student’s paired t-test was used to compare the changes after sleep deprivation and then after yogic relaxation. Results: Overnight sleep deprivation resulted in statistically significant (P &lt; 0.05) increases in systolic BP (SBP), low frequency (LF), LF/high frequency (HF), diastolic BP (DBP), PSS, and mean HR. This was coupled with significant decreases in mean RR, SDNN, pNN50, HF, and RMSSD. Following yogic relaxation, these changes were reversed, and significant decreases were witnessed in LF, LF/ HF, SBP, mean HR, DBP, and PSS with significant increases in mean RR, pNN50, HF, RMSSD, and SDNN. Conclusion: The findings of our study reiterate the negative effects of sleep deprivation on cardiac autonomic status. Such deleterious effects may be partially reversed by practicing yogic relaxation (Shavasana). Such conscious relaxation may be able to help correct imbalance of autonomic nervous system by enhancing parasympathetic tone and reducing sympathetic overactivity.

Heart disease is the major cause of death today. Cholesterol, blood pressure and CVD cardiovascular disease. Pulse rate are the main reason for the heart disease. Measurement of heart rate variability (HRV) its shows information on the functional state of the autonomic nervous system (sympathetic and parasympathetic). HR analysis based on measure of heart rate signal per unit of time of the number of heartbeats (identified as RR interval, as it is the time interval between successive R points of the QRS complex of the electrocardiogram and measured by the variation in the beat-to-beat interval).Heart rate variability (HRV) is a relatively new method for assessing the effects of stress on your body. It is measured as the time gap between your heart beats that varies as you breathe in and out. The heart is a key factor of the human body, acting as a pump that transfers oxygenated and deoxygenated blood around the body. Like all other organs, it is susceptible to diseases and age. Heart rate variability is a reliable indication of the many physiological factors modulating the normal rhythm of the heart. In fact, they provide a powerful means of observing the relationship between the sympathetic and parasympathetic nervous systems. It is also significantly associated with average heart rate (HR), therefore, HRV actually provides information on two quantities, that is, on HR and its variability.

This study is aimed to determine significant physiological parameters of brain and heart under meditative state, both in each activities and their dynamic correlations. Electrophysiological changes in response to meditation were explored in 12 healthy volunteers who completed 8 weeks of a basic training course in autogenic meditation. Heart coherence, representing the degree of ordering in oscillation of heart rhythm intervals, increased significantly during meditation. Relative EEG alpha power and alpha lagged coherence also increased. A significant slowing of parietal peak alpha frequency was observed. Parietal peak alpha power increased with increasing heart coherence during meditation, but no such relationship was observed during baseline. Average alpha lagged coherence also increased with increasing heart coherence during meditation, but weak opposite relationship was observed at baseline. Relative alpha power increased with increasing heart coherence during both meditation and...

Guidelines report that the optimal treatment for ST-elevation myocardial infarction (STEMI) is a primary percutaneous coronary intervention (PPCI) when performed timely by trained operators. Yet, the reopening of the infarct-related artery (IRA) is not always followed by myocardial reperfusion. This phenomenon is most commonly called &quot;no-reflow&quot;, is caused by microvascular obstruction (MVO) and is associated to a worse outcome. Electrocardiogram (ECG) is crucial for the diagnosis of STEMI, but is also useful for the assessment of MVO. In this review we summarize ECG-derived parameters associated to MVO and their prognostic relevance.

—The paradigm change from delayed interventional to Predictive, Preventive and Personalized Medicine is a leading global challenge in the 21st century. Ubiquitous convergence of mobile applications, new intelligent sensors and machine learning methods make possible creation of new generation personalized automatic healthcare monitoring and pathologies detection systems. These systems will help to make platforms for more effective treatments tailored to the person, that is considered as the "medicine of the future". Implementation of these latest trends in medicine will make it possible to detect health deterioration remotely and will avoid millions of hospitalizations costing billions of dollars in the world every year. In the article the problem of cardiovascular diseases and the state of healthcare industry is described and general architecture of automatic system for heart pathologies detection is proposed.

The aim of this study is to investigate the bodily-self in Restrictive Anorexia, focusing on two basic aspects related to the bodily self: autonomic strategies in social behavior, in which others' social desirability features, and social cues (e.g., gaze) are modulated, and interoception (i.e., the sensitivity to stimuli originating inside the body). Furthermore, since previous studies carried out on healthy individuals found that interoception seems to contribute to the autonomic regulation of social behavior, as measured by Respiratory Sinus Arrhythmia (RSA), we aimed to explore this link in anorexia patients, whose ability to perceive their bodily signal seems to be impaired. To this purpose, we compared a group of anorexia patients (ANg; restrictive type) with a group of Healthy Controls (HCg) for RSA responses during both a resting state and a social proxemics task, for their explicit judgments of comfort in social distances during a behavioral proxemics task, and for their Interoceptive Accuracy (IA). The results showed that ANg displayed significantly lower social disposition and a flattened autonomic reactivity during the proxemics task, irrespective of the presence of others' socially desirable features or social cues. Moreover, unlike HCg, the autonomic arousal of ANg did not guide behavioral judgments of social distances. Finally, IA was strictly related to social disposition in both groups, but with opposite trends in ANg. We conclude that autonomic imbalance and its altered relationship with interoception might have a crucial role in anorexia disturbances.

Ususret obilježavanju 119. obljetnice smrti dr. Ante Starčevića, u organizaciji Hrvatske stranke prava dr. Ante Starčević (HSP AS)
otvorena je, u suradnji sa Narodnim m u z e j o m Z a d a r i Z n a n s t v e n o m knjižnicom Zadar, u prostorijama Gradske lože u Zadru 20. veljače 2015. izložba slika, postera, knjiga, arhivskog, filatelističkog, numizmatičkog i ostalog kolekcionarskog materijala pod nazivom Dr. Ante Starčević –
Otac domovine. Među nizom zanimljivih se izložaka posebno isticala vojna oznaka za rukav pod eponimnim imenom Brigada dr. Ante Starčević – Gornji Vakuf.

In this work, the arrhythmias in the electrocardiograph (ECG) signals are analyzed by using multi-layer perceptron (MLP) network. For training MLP network back-propagation with adaptive learning rate method is used. Feature vectors obtained from consecutive sample values of each peak in different window sizes are normalized and used for training the networks. Performances of different classifiers are examined depending on

Background and Objective: Heart rate variability parameters are studied by the research community as potential valuable indices for seizure detection and anticipation. This paper investigates heart activity abnormalities during focal epileptic seizures in childhood. Methods: Seizures affect both the sympathetic and parasympathetic system which is expressed as abnormal patterns of heart rate variability (HRV) parameters. In the present study, a clinical dataset containing 42 focal seizures in long-term electrocardiographic (ECG) recordings from drug-resistant pediatric epileptic patients (with age 8.2 ± 4.3 years) was analyzed. Results: Results indicate that the time domain HRV parameters (heart rate, SDNN, standard deviation of heart rate, upper envelope) and spectral HRV parameters (LF/HF, normalized HF, normalized LF, total power) are significantly affected during ictal periods. The HRV features were ranked in terms of their relevance and efficacy to discriminate non-ictal/ictal periods and the top-ranked features were selected using the minimum Redundancy Maximum Relevance algorithm for further analysis. Then, a personal-ized anticipation algorithm based on multiple regression was introduced providing an "epileptic index" of imminent seizures. The performance of the system resulted in anticipation accuracy of 77.1% and an anticipation time of 21.8 s. Conclusions: The results of this analysis could permit the anticipation of focal seizures only using elec-trocardiographic signals and the implementation of seizure anticipation strategies for a range of real-life clinical applications.

Using spiroarteriocardiorhythmography, 202 highly qualified male athletes aged 22.6 ± 2.8 years, who are representatives of acyclic sports were examined. According to HRV (hearth rate variability), the types of the athletes' cardiac rhythm regulation were determined. There are 4 types of autonomic regulation of cardiac rhythm: Type I-indicates moderate stress, Type II-indicates a decrease in the functional state of regulatory systems, the development of fatigue, Type III-indicates the optimal state of regulation, Type IV-indicates overstrain of autonomic regulation or high fitness. The athletes with a predominance of central (types I and II) and autonomous (types III and IV) effects on the cardiac rhythm regulation are differentiated by indicators of total respiration power (TP R , (l/min) 2) and power in the high frequency range (HF R), (l/min) 2). Athletes with the type IV cardiac rhythm regulation had a more significant contribution of the low-frequency component (LF R n, n.u.) in the regulation of spontaneous respiration than athletes with type I and II cardiac rhythm regulation. In the type II regulation of cardiac rhythm there is a significant decrease in expiratory duration (s), which is also manifested by a significant increase in the ratio of inspiratory and expiratory phases, which may characterize expiratory insufficiency for this type.

Gender recognition is trivial for a physiotherapist, but it is considered a challenge for computers. The electromyography (EMG) and heart rate variability (HRV) were utilized in this work for gender recognition during exercise using a stepper. The relevant features were extracted and selected. The selected features were then fused to automatically predict gender recognition. However, the feature selection for gender classification became a challenge to ensure better accuracy. Thus, in this paper, a feature selection approach based on both the performance and the diversity between the two features from the rank-score characteristic (RSC) function in a combinatorial fusion approach (CFA) (Hsu et al.) was employed. Then, the features from the selected feature sets were fused using a CFA. The results were then compared with other fusion techniques such as naive bayes (NB), decision tree (J48), k-nearest neighbor (KNN) and support vector machine (SVM). Besides, the results were also compared with previous researches in gender recognition. The experimental results showed that the CFA was efficient and effective for feature selection. The fusion method was also able to improve the accuracy of the gender recognition rate. The CFA provides much better gender classification results which is 94.51% compared to Barani's work (90.34%), Nazarloo's work (92.50%), and other classifiers.