Short-term Heart Rate Variability Analysis Research Articles

Non-Contact Short-Term Heart Rate Variability Analysis Under Paced Respiration Based on a Robust Fiber Optic Sensor System

Non-Contact Short-Term Heart Rate Variability Analysis Under Paced Respiration Based on a Robust Fiber Optic Sensor System

Reliability and Validity of Kubios HRV Smart Phone Application as Measures of Heart Rate Variability

Introduction: Heart rate variability (HRV) analysis has given a non-invasive way for assessing cardiac autonomic control. Reduced HRV is an independent indicator of poor prognosis in both heart disease patients and the general population. Aim/Objective: To establish reliability and validity for Kubios HRV smart phone application. Materials and methods: Fifty (n =50) office workers volunteered for the study, with 10 females and 40 males ranging in age from 30 to 50 years (Mean age =38.4±5.6). To evaluate Intra and Inter-rater reliability and validity the of HRV parameter, R-R intervals comparing simultaneous recording from ECG and Kubios HRV app, at different three times (day1,day2 &day3) one day apart and by two different trained examiners in the same participants. Each participants rested in supine for 10 minutes prior to the assessment and was instructed to remain relaxed, breathe properly, and refrain from talking and sleeping during the measurement. The RR intervals (R-R) were recorded during a 5 min period in supine position using ECG and polar H10 monitor with Kubios HRV smartphone application. Results: Kubios HRV smart phone application shows excellent reliability, Intra-rater (α =0.868) and Inter-rater (α =0.890) and Validity (r = 0.94) with R-R intervals calculated from ECG. Conclusion: The Kubios HRV smart phone application provides an accurate and reliable alternative to the ECG for acquiring inter-beat interval time series data. The Kubios HRV app gives an R-R interval that can be used for short term HRV analysis in office workers from steady resting conditions, supporting the selection of this approach of evaluation in research and clinical practise.

Assessment of sympathovagal balance by HRV analysis in alcoholic and nonalcoholic fatty liver disease patients

BACKGROUND: Heart rate variability (HRV) is the variation in the time intervals between continuous heartbeats also called interbeat intervals to give information related to the heart, blood pressure, gaseous exchange, and sympathetic and parasympathetic balance. Abnormalities in the conduction of the cardiac system alter the measurements of heart rate variability and lead to alteration in autonomic function with a higher risk of mortality. So, our objective includes the assessment of sympathovagal balance in AFLD and NAFLD patients. MATERIALS AND METHODS: The study included 78 alcoholic and 54 nonalcoholic fatty liver patients. A room temperature of 23°C with 25–35% humidity will be maintained in a recording room. Basal supine heart rate and BP will be recorded by the oscillometric method using an automated blood pressure monitor Omron MX3, India. Lead II ECG will be recorded for the next 5 minutes in total resting condition for short-term HRV analysis. Short-term HRV indices including time domain and frequency domain were recorded from each patient. Under time domain, SDNN, RMSSD, and average RR were noted. Under frequency domain, LF, HF, VLF, LF (nu), HF (nu), and LF/HF were calculated. The data were collected by using a 16-bit, power lab 8/30 data acquisition system (New South Wales, Australia) with acknowledge 3.8.2 software. Inferential analyses such as independent t-tests and Mann–Whitney tests were used to compare NAFLD and AFLD patient groups. Carl Pearson correlation analysis was performed to obtain a relationship between variables. RESULTS: SDNN in (ms) which represents the overall HRV found to be decreased in both alcoholic (32.84 ± 79.08) and nonalcoholic fatty liver disease (22.04 ± 13.85) compared to the normal range (50 ± 16)) from 27 studies. The value of RMSSD in (ms) was decreased in both alcoholic (17.00 ± 12.48) and nonalcoholic fatty liver disease patients (14.00 ± 9.44) with the normal range of (42 ± 15) from 15 studies. Pearson correlation analysis showed the age of AFLD patients significantly and positively correlated with average RR. Pearson correlation analysis for the age of NAFLD patients was significantly and positively correlated with the average RR, HF, SDNN, RMSSD, and LF. CONCLUSION: Altered autonomic activity was noted in both alcoholic and nonalcoholic fatty liver disease patients. An early prognosis of fatty liver is very necessary to prevent the disease progress into later fatal life-threatening stages.

Impact of subtetanic neuromuscular electrical stimulation on cardiac autonomic nervous system in young individuals.

Although subtetanic neuromuscular electrical stimulation (NMES) has been proposed as an exercise training and/or rehabilitation tool, the impact of NMES on the autonomic nervous system (ANS) is unclear. Thus, we hypothesized that NMES would alter ANS, i.e., increase sympathetic activity and decrease parasympathetic activity, in young individuals. Eighteen healthy young individuals (16 males, mean age: 22 [SD: 4] years, Body Mass Index: 21.7 [2.2] kg/m2) volunteered. Blood pressure (BP), heart rate (HR), and R-R intervals were recorded during 6-minute resting, NMES, and recovery conditions. Short-term heart rate variability analysis of R-R intervals was performed for the frequency and time domains during each condition. Time domain indices included the root mean square of successive R-R interval differences (RMSSD), and the percentage of successive R-R intervals differing by more than 50ms (pRR50%). Frequency domain indices (fast Fourier transform) of R-R intervals included total power (TP), low-frequency (LF) power (0.04-0.15 Hz), and high-frequency (HF) power (0.15-0.4 Hz). BP was not altered but HR was significantly increased during NMES (P<0.001), and it returned to the resting level at recovery. RMSSD and pRR50 decreased from resting to NMES and returned at recovery conditions (P<0.05, respectively). TP and HF decreased from resting to NMES and returned at recovery conditions (P<0.05, respectively). LF increased from NMES to recovery (P<0.05). The LF/HF ratio showed no significant differences between conditions (P=0.210). Cardiac ANS fluctuated by subtetanic NMES without BP elevation in healthy young individuals. Parasympathetic but not sympathetic activity was affected by NMES stimulation.

Assessment of Cardiac Autonomic Function in Women With Polycystic Ovary Syndrome Through Ewing's Battery, Heart Rate Variability Analysis, and Composite Autonomic Symptom Score-31 Scale.

Introduction Polycystic ovary syndrome (PCOS) is a frequently occurringendocrine condition prevalent in women of reproductive age characterized by chronic anovulation, hyperandrogenism, insulin resistance, and a low-grade inflammatory state. Patients with PCOS are more vulnerable to developing cardiac and metabolic co-morbidities. Sympathetic overactivity is also reported in PCOS patients. Objective This study aimed to assess cardiac autonomic function in PCOS by Heart Rate Variability Analysis, Ewing's Test, and Composite Autonomic Symptom Scale-31 (COMPASS-31). Methods Thirty female PCOS patients and 30 age-matched control females were enrolled in the study. Both cases and controls were subdivided into sub-groups based on body mass index (BMI) and waist-to-hip ratio (WHR). The cardiac autonomic functions were assessed by the COMPASS-31 questionnaire, Ewing's battery tests, and short-term heart rate variability analysis. Results There was no significant difference in age, BMI, and WHR of both groups. Additionally, cases had a significantly higher low frequency to high frequency (LF/HF) ratio and COMPASS-31 score andalsoreported more derangement in Ewing's battery test, indicating cardiac autonomic dysfunction in PCOS patients. Conclusion Patients with PCOS are more prone to developing cardiac and metabolic co-morbidities.Early assessment of cardiac autonomic function can prevent future complications with timely interventions. Altered autonomic function in PCOS patients can be due to hyperandrogenism and insulin resistance.

Validity of the Pneumonitor for RR intervals acquisition for short-term heart rate variability analysis extended with respiratory data in pediatric cardiac patients.

Breathing pattern alterations change the variability and spectral content of the RR intervals (RRi) on electrocardiogram (ECG). However, there is no method to record and control participants' breathing without influencing its natural rate and depth in heart rate variability (HRV) studies. This study aimed to assess the validity of the Pneumonitor for acquisition of short-term (5 minutes) RRi in comparison to the reference ECG method for analysis of heart rate (HR) and HRV parameters in the group of pediatric patients with cardiac disease. Nineteen patients of both sexes participated in the study. An ECG and Pneumonitor were used to record RRi in 5-minute static rest conditions, the latter also to measure the relative tidal volume and respiratory rate. The validation comprised Student's t-test, Bland-Altman analysis, intraclass correlation coefficient, and Lin's concordance correlation. The possible impact of respiratory activity on the agreement between ECG and the Pneumonitor was also assessed. An acceptable agreement for the number of RRi, mean RR, hazard ratio (HR), and HRV measures calculated based on RRi acquired using the ECG and Pneumonitor was presented. There was no association between the breathing pattern and RRi agreement between devices. The Pneumonitor might be considered appropriate for cardiorespiratory studies in the group of pediatric cardiac patients in rest condition.

Heart rate variability modifications in adult patients with early versus late-onset temporal lobe epilepsy: A comparative observational study

ObjectivesTemporal lobe epilepsy (TLE) is the most frequent form of focal epilepsy. TLE is associated with cardio-autonomic dysfunction and increased cardiovascular (CV) risk in patients over the fifth decade of age. In these subjects, TLE can be classified as early-onset (EOTLE; i.e., patients who had developed epilepsy in their youth) and late-onset (LOTLE; i.e., patients who developed epilepsy in adulthood). Heart rate variability (HRV) analysis is useful for assessing cardio-autonomic function and identifying patients with increased CV risk. This study compared changes in HRV occurring in patients over the age of 50, with EOTLE or LOTLE. MethodsWe enrolled twenty-seven adults with LOTLE and 23 with EOTLE. Each patient underwent a EEG and EKG recording during 20-minutes of resting state and a 5-minutes hyperventilation (HV). Short-term HRV analysis was performed both in time and frequency domains. Linear Mixed Models (LMM) were used to analyze HRV parameters according to the condition (baseline and HV) and group (LOTLE and EOTLE groups). ResultsCompared to the LOTLE group, the EOTLE group showed significantly decreased LnRMSSD (natural logarithm of the root mean square of the difference between contiguous RR intervals) (p-value=0.05), LnHF ms2 (natural logarithm of high frequency absolute power) (p-value=0.05), HF n.u. (high frequency power expressed in normalized units) (p-value=0.008) and HF% (high frequency power expressed in percentage) (p-value=0.01). In addition, EOTLE patients exhibited increased LF n.u. (low frequency power expressed in normalized units) (p-value=0.008) and LF/HF (low frequency/high frequency) ratio (p-value=0.007). During HV, the LOTLE group exhibited a multiplicative effect for the interaction between group and condition with increased LF n.u. (p = 0.003) and LF% (low frequency expressed in percentage) (p = 0.05) values. ConclusionsEOTLE is associated with reduced vagal tone compared to LOTLE. Patients with EOTLE may have a higher risk of developing cardiac dysfunction or cardiac arrhythmia than LOTLE patients.

AN EFFECTIVE DEEP LEARNING BASED APPROACH TO MEASURE INTERDEPENDENCE OF HEART RATE VARIABILITY ANALYSIS AND R-PEAKS

&#x0D; &#x0D; &#x0D; Heart rate variability (HRV) is the physiological phenomenon to measure variations between consecutive heartbeats. HRV analysis has been used to analyse and detect different cardiac diseases that rely on R-peaks' reliability and accurate detection. Myocardial infarction (MI) is a main cardiac disease that causes irregularity in heartbeats and some non-specific abnormalities occur in the recorded ECG, including ST changes and T-wave alternans. These abnormalities may be ignored by considering minor changes that can lead to delayed diagnosis. Therefore, the analysis of these abnormalities is a challenging task. This study investigated these non-specific abnormalities to recognize MI patterns based on HRV analysis highlighting the importance of R-peaks detection accuracy. Short-term HRV analysis of two publicly available datasets, MIT-BIH ST Changes and European ST-T changes was performed based on R-peaks detected from ECG signals. R-peaks detection achieved an averaged 99.77% sensitivity, 99.49% positive predictability and 99.32% accuracy for MIT-BIH ST changes dataset whereas for European ST-T changes dataset, 99.85% sensitivity, 99.41% positive predictability, and 99.28% accuracy was achieved. Subsequently, HRV parameters were computed from both datasets and data fusion was performed followed by a deep learning model to find out the most accurate pattern recognition results. For pattern recognition, a finely tuned artificial neural network was applied to HRV parameters, in two scenarios. For both scenarios, an accuracy greater than 99% was achieved. Furthermore, linear regression was also performed on computed HRV measures in both scenarios that observed a similarity of 97% between both datasets. The importance of reliable and accurate R-peaks detection for HRV analysis to analyse and detect different cardiovascular diseases was elaborated in the end.&#x0D; &#x0D; &#x0D;

The Autonomic Imbalance of Myocardial Ischemia during Exercise Stress Testing: Insight from Short-Term Heart Rate Variability Analysis.

Exercise stress testing (EST) has limited power in diagnosing obstructive coronary artery disease (CAD). The heart rate variability (HRV) analysis might increase the sensitivity of CAD detection. This study aimed to evaluate the correlation between short-term HRV and myocardial ischemia during EST, including the acceleration, maximum, and recovery stages of heart rate (HR). The HRV during EST from 19 healthy (RHC) subjects and 35 patients with CAD (25 patients with insignificant CAD (iCAD), and 10 patients with significant CAD (sCAD)) were compared. As a result, all HRV indices decreased at the maximum stage and no significant differences between iCAD and sCAD were found. The low-frequency power of heart rate signal (LF) of the RHC group recovered relatively quickly from the third to the sixth minutes after maximum HR, compared with that of the sCAD group. The relative changes of most HRV indices between maximum HR and recovery stage were lower in the sCAD group than in the RHC group, especially in LF, the standard deviation of all normal to normal intervals (SDNN), and the standard deviation in the long axis direction of the Poincaré plot analysis (SD2) indices (p &lt; 0.05). The recovery slope of LF was significantly smaller in the sCAD group than in the RHC group (p = 0.02). The result suggests that monitoring short-term HRV during EST provides helpful insight into the cardiovascular autonomic imbalance in patients with significant CAD. The relative change of autonomic tone, especially the delayed sympathetic recovery, could be an additional marker for diagnosing myocardial ischemia.

Effects of a Combined Intradialytic Exercise Training Program and Music on Cardiac Autonomic Nervous System Activity in Hemodialysis Patients.

This study aimed to examine the effect of an intradialytic exercise program in combination with music on heart rate variability (HRV) indices and functional capacity in patients on maintenance hemodialysis (HD). Methods: Forty HD patients were randomized to four training groups for six months: the combined music and exercise group (Group A), the exercise group (Group B), the music group (Group C), and the control group (Group D). At baseline and after 6 months, all participants underwent both short- (for 30 min) and long- (for 24 h) term measurements of HRV and functional capacity assessment with a 6 min walking test (6MWT). Patients of groups A and C listened to preferred music. Results: Long-term HRV analysis showed that standard deviation of all normal-to-normal RR intervals (SDNN) and the square root of the mean squared differences of successive RR intervals (rMSSD) were significantly higher at the end of the study in groups A (by 13.2% and 47.3%), B (by 15.1% and 50%), and C (by 9.0% and 30.1%), compared to group D (p < 0.05). Values of rMSSD and percentage of RR intervals differing by more than 50 ms from the preceding RR interval (pNN50) were elevated in groups A (by 35.6% and 142.9%), B (by 36.1% and 75%), and C (by 15.2% and 28.6%), compared to baseline measurements (p < 0.05). Also, pNN50 was increased in group A compared to groups B (by 21.4%), C (by 88.9%), and D (by 142.9%) (p < 0.05). Similar results were noted by short-term HRV analysis. Functional capacity was improved at the end of the 6-month study in groups A (by 20.3% and 25.7%) and B (by 15.8% and 21.1%) compared to groups C and D (p < 0.05). Conclusions: Intradialytic exercise combined with music-listening can improve the functional capacity and cardiac autonomic nervous system activity in hemodialysis patients.

Mental Stress Assessment Using Ultra Short Term HRV Analysis Based on Non-Linear Method.

Mental stress is on the rise as one of the major health problems in modern society. It is important to detect and manage mental stress to prevent various diseases caused by stress and to maintain a healthy life. The purpose of this paper is to present new heart rate variability (HRV) features based on empirical mode decomposition and to detect acute mental stress through short-term HRV (5 min) and ultra-short-term HRV (under 5 min) analysis. HRV signals were acquired from 74 young police officers using acute stressors, including the Trier Social Stress Test and horror movie viewing, and a total of 26 features, including the proposed IMF energy features and general HRV features, were extracted. A support vector machine (SVM) classification model is used to classify the stress and non-stress states through leave-one-subject-out cross-validation. The classification accuracies of short-term HRV and ultra-short-term HRV analysis are 86.5% and 90.5%, respectively. In the results of ultra-short-term HRV analysis using various time lengths, we suggest the optimal duration to detect mental stress, which can be applied to wearable devices or healthcare systems.

A Bayesian Dynamic Inference Approach Based on Extracted Gray Level Co-Occurrence (GLCM) Features for the Dynamical Analysis of Congestive Heart Failure

The adoptability of the heart to external and internal stimuli is reflected by heart rate variability (HRV). Reduced HRV can be a predictor of post-infarction mortality. In this study, we propose an automated system to predict and diagnose congestive heart failure using short-term heart rate variability analysis. Based on the nonlinear, nonstationary, and highly complex dynamics of congestive heart failure, we extracted multimodal features to capture the temporal, spectral, and complex dynamics. Recently, the Bayesian inference approach has been recognized as an attractive option for the deeper analysis of static features, in order to perform a comprehensive analysis of extracted nodes (features). We computed the gray level co-occurrence (GLCM) features from congestive heart failure signals and then ranked them based on ROC methods. This study focused on utilizing the dissimilarity feature, which is ranked as highly important, as a target node for the empirical analysis of dynamic profiling and optimization, in order to explain the nonlinear dynamics of GLCM features extracted from heart failure signals, and distinguishing CHF from NSR. We applied Bayesian inference and Pearson’s correlation (PC). The association, in terms of node force and mapping, was computed. The higher-ranking target node was used to compute the posterior probability, total effect, arc contribution, network profile, and compression. The highest value of ROC was obtained for dissimilarity, at 0.3589. Based on the information-gain algorithm, the highest strength of the relationship was obtained between nodes “dissimilarity” and “cluster performance” (1.0146), relative to mutual information (81.33%). Moreover, the highest relative binary significance was yielded for dissimilarity for 1/3rd (80.19%), 2/3rd (74.95%) and 3/3rd (100%). The results revealed that the proposed methodology can provide further in-depth insights for the early diagnosis and prognosis of congestive heart failure.

Reduction of Cardiac Autonomic Modulation and Increased Sympathetic Activity by Heart Rate Variability in Patients With Long COVID.

Although several clinical manifestations of persistent long coronavirus disease (COVID-19) have been documented, their effects on the cardiovascular and autonomic nervous system over the long term remain unclear. Thus, we examined the presence of alterations in cardiac autonomic functioning in individuals with long-term manifestations. The study was conducted from October 2020 to May 2021, and an autonomic assessment was performed to collect heart rate data for the heart rate variability (HRV) analysis. The study participants were divided into the long COVID clinical group, the intragroup, which included patients who were hospitalized, and those who were not hospitalized and were symptomatic for different periods (≤3, >3, ≤6, and >6 months), with and without dyspnoea. The control group, the intergroup, comprised of COVID-free individuals. Our results demonstrated that the long COVID clinical group showed reduced HRV compared with the COVID-19-uninfected control group. Patients aged 23–59 years developed COVID symptoms within 30 days after infection, whose diagnosis was confirmed by serologic or reverse-transcription polymerase chain reaction (swab) tests, were included in the study. A total of 155 patients with long COVID [95 women (61.29%), mean age 43.88 ± 10.88 years and 60 men (38.71%), mean age 43.93 ± 10.11 years] and 94 controls [61 women (64.89%), mean age 40.83 ± 6.31 and 33 men (35.11%), mean age 40.69 ± 6.35 years] were included. The intragroup and intergroup comparisons revealed a reduction in global HRV, increased sympathetic modulation influence, and a decrease in parasympathetic modulation in long COVID. The intragroup showed normal sympathovagal balance, while the intergroup showed reduced sympathovagal balance. Our findings indicate that long COVID leads to sympathetic excitation influence and parasympathetic reduction. The excitation can increase the heart rate and blood pressure and predispose to cardiovascular complications. Short-term HRV analysis showed good reproducibility to verify the cardiac autonomic involvement.

Accuracy Assessment of Oura Ring Nocturnal Heart Rate and Heart Rate Variability in Comparison With Electrocardiography in Time and Frequency Domains: Comprehensive Analysis.

BackgroundPhotoplethysmography is a noninvasive and low-cost method to remotely and continuously track vital signs. The Oura Ring is a compact photoplethysmography-based smart ring, which has recently drawn attention to remote health monitoring and wellness applications. The ring is used to acquire nocturnal heart rate (HR) and HR variability (HRV) parameters ubiquitously. However, these parameters are highly susceptible to motion artifacts and environmental noise. Therefore, a validity assessment of the parameters is required in everyday settings.ObjectiveThis study aims to evaluate the accuracy of HR and time domain and frequency domain HRV parameters collected by the Oura Ring against a medical grade chest electrocardiogram monitor.MethodsWe conducted overnight home-based monitoring using an Oura Ring and a Shimmer3 electrocardiogram device. The nocturnal HR and HRV parameters of 35 healthy individuals were collected and assessed. We evaluated the parameters within 2 tests, that is, values collected from 5-minute recordings (ie, short-term HRV analysis) and the average values per night sleep. A linear regression method, the Pearson correlation coefficient, and the Bland–Altman plot were used to compare the measurements of the 2 devices.ResultsOur findings showed low mean biases of the HR and HRV parameters collected by the Oura Ring in both the 5-minute and average-per-night tests. In the 5-minute test, the error variances of the parameters were different. The parameters provided by the Oura Ring dashboard (ie, HR and root mean square of successive differences [RMSSD]) showed relatively low error variance compared with the HRV parameters extracted from the normal interbeat interval signals. The Pearson correlation coefficient tests (P<.001) indicated that HR, RMSSD, average of normal heart beat intervals (AVNN), and percentage of successive normal beat-to-beat intervals that differ by more than 50 ms (pNN50) had high positive correlations with the baseline values; SD of normal beat-to-beat intervals (SDNN) and high frequency (HF) had moderate positive correlations, and low frequency (LF) and LF:HF ratio had low positive correlations. The HR, RMSSD, AVNN, and pNN50 had narrow 95% CIs; however, SDNN, LF, HF, and LF:HF ratio had relatively wider 95% CIs. In contrast, the average-per-night test showed that the HR, RMSSD, SDNN, AVNN, pNN50, LF, and HF had high positive relationships (P<.001), and the LF:HF ratio had a moderate positive relationship (P<.001). The average-per-night test also indicated considerably lower error variances than the 5-minute test for the parameters.ConclusionsThe Oura Ring could accurately measure nocturnal HR and RMSSD in both the 5-minute and average-per-night tests. It provided acceptable nocturnal AVNN, pNN50, HF, and SDNN accuracy in the average-per-night test but not in the 5-minute test. In contrast, the LF and LF:HF ratio of the ring had high error rates in both tests.

Short-term Heart Rate Variability Analysis in Healthy Dogs of Different Ages

Background: The modulation of heart rate by autonomic nervous system may be evaluated by the heart rate variability (HRV), which illustrates the fluctuations between RR intervals. To evaluate this analysis, the intervals between 2 QRS complexes are measured. In general, high HRV values are expected in healthy individuals; otherwise, low values are indicative of organism dysfunction. Studies conducted in healthy humans show that HRV suffers reduction with ageing and that there is autonomic immaturity in neonates. The aim of this study was to describe the characteristic pattern of cardiac autonomic behavior in healthy dogs in different age groups through short-term HRV analysis.Materials, Methods &amp; Results: A total of 87 healthy dogs were studied. HRV was analyzed in time and frequency domain, using Holter and heart rate monitor. It was observed that puppies (below one year old) presented a lower parasympathetic predominance and, consequently, lower HRV values on time domain (SDNN, PNN50% e RMSSD) compared to the other 2 groups and on frequency domain (LF, HF and LF/HF) compared to the adult animals group (between 1 and 7-year-old), which presented higher HRV values when compared to the other groups. Elderly dogs (over 8-year-old) exhibited a natural tendency to decrease cardiac parasympathetic HRV indexes.Discussion: The use of the HRV method as a prognostic index and as an arrhythmogenic marker for various canine heart diseases presents interesting perspectives. However, before it may be employed for these purposes, a better understanding should be established regarding the physiological behavior of autonomic cardiac modulation in different age groups to serve as a basis for future analyses. This study observed that puppies presented higher values for HR and, therefore, shorter RR intervals than the other groups (adult and elderly dogs), what was observed on Holter and heart rate monitor methods (HRM). There were significant differences between puppies and the other 2 groups (adults and elderly) for all time-domain variables using both methods (Holter and HRM methods). SDNN was significantly lower in puppies compared to adults and elderly dogs. In addition, both RMSSD and PNN50%, which were more reliable over shorter periods of time, also presented means and medians that were significantly lower in puppies. Regarding frequency-domain HRV parameters observed on Holter method, these indexes were decreased on the elderly group compared to adult dogs, which is a possible effect of aging. Also, puppies revealed lower frequency-domain HRV parameters on both methods when compared to adult dogs. The influence of age on HRV is possibly related to the stage of development of an individual, starting at conception up to the maturity in relation to the mechanisms that cause variations in HR. There are studies in humans that suggest a gradual increase in parasympathetic activity during childhood, followed by a steady decrease as aging occur. The present study observed the same pattern in dogs. The balance between sympathetic and parasympathetic systems is influenced by age in dogs, which alters HRV values in the short-term. The HRV method´s analysis is relatively simple and non-invasive for assessing cardiac autonomic function; also, it is widely used in human medicine as a risk measure for sudden cardiac death. The 24-hour HRV analysis is highly challenging, as it is time-consuming, expensive, delays diagnosis, and has a large number of artifacts; in this way, standards for its short-term analysis were developed. Keywords: cardiology, autonomic nervous system, heart rate monitor, Holter.

Aging effect on cardiac sympathovagal activity in healthy males over seven decades using short-term heart rate variability analysis

Aging effect on cardiac sympathovagal activity in healthy males over seven decades using short-term heart rate variability analysis

Quantitative assessment of autonomic nervous system responses induced by graded training workloads in healthy elderly, through indices obtained from heart rate variability analysis

Abstract Background Quantitative assessment of individual body adaptability to physical training performed with the purposes of health maintenance is particularly necessary in the elderly age, to avoid the risk of overstrain induced by inappropriate exercises workload and physical stress. For that purpose, heart rate monitors and heart rate variability (HRV) analysis are nowadays commercially available. However, their reliability to guide individualized fitness training in elderly people needs to be tested, knowing that users might not have medical education. Objective To preliminary quantify autonomic nervous system (ANS) responses to graded physical effort and recovery in healthy elderly basing on the parasympathetic nervous system (PNSi), the sympathetic nervous system (SNSi) and the stress (STRi) indices, derived by short-term and time-varying HRV analysis. Methods ECG of a 75 healthy male subject was monitored, from April to November 2020, during three times/week training sessions with a professional bike–ergometer. Each session consisted of 10 minutes baseline rest, 5 minutes warm-up, 30 minutes work and 10 minutes recovery. According to age, the training workload was graded from low (65–75 watt/min), to moderate (75–85 watt/min), semi-intensive (85–95 watt/min) and intensive (95–110 watt/min). For this pilot study, ECG data of only 40 training sessions (10 sessions for each workload to evaluate reproducibility) were analyzed with Kubios Premium software (version 3.4.1), in the time (TD) and frequency (FD) domains, with nonlinear (NL) methods and with time-varying (TV) algorithms. Short-time HRV was calculated from 2-minutes intervals. The PNSi, SNSi and STRi induced by each workload were averaged and compared. Results Average values of PNSi, SNSi and STRi were significantly different (p&amp;lt;0.05) among training sessions carried out with different workloads (Table 1A) and among measurements obtained at rest, at every 5 minutes step of each 30 minutes training session, and at 1 and 5 minutes of recovery (Table 1B). Interestingly, the correlation between SNSi and STRi was strictly linear (R= 0,98), whereas that between PNSi and STRi was better fitted by a cubic function (R=0,82 with cubic vs 0.68 with linear function), when evaluated either as a function of the sessions' workloads (Figure 1A), or of four time-intervals of each training session (Figure 1B). PNSi and SNSi were inversely correlated, with cross-point at about 15 minutes of training and 75 watt/min workload. Conclusions The calculation of PNSi, SNSi and STRi from HRV analysis is an efficient method for quick and simplified quantitative assessment of dynamic ASN adaptation to effort-induced stress from HRV analysis. If confirmed, the method may be useful for safer and even remote monitoring of training/rehabilitation in elderly. However, more detailed evaluation of spectral and NL parameters may be necessary to interpret more complex patterns of abnormal cases. Funding Acknowledgement Type of funding sources: None. Table 1Figure 1

CHRONIC OBSTRUCTIVE PULMONARY DISEASE: GRADING OF SEVERITY AS REFLECTED BY SHORT TERM HEART RATE VARIABILITY.

Chronic obstructive pulmonary disease (COPD) is a broad spectrum respiratory illness where there are structural and functional changesin the lungs. According to WHO, COPD is a leading global burden and by 2030 it will be the third leading cause of death worldwide. The structural and functional changes in the lungs in COPD patients tend to inuence the cardiac autonomic functions and heart rate variability (HRV). Previousstudiesshow that there is decrease in heart rate variability in COPD patients. In many previousstudies, it isfound that results ofshort term HRV analysis of 5minutes is comparable to standard 24hours HRV analysis and is very patient friendly and reproducible procedure to analyse the cardiac autonomic functions. So determination of parameters of cardiac autonomic functions with the help of short term HRV analysis in COPD patients is helpful in determining the pathophysiology and subsequent management of such patients. A Descriptive and observational study was conducted upon 100 previously diagnosed COPD patients at the Autonomic function research Laboratory, Department of Physiology, R G Kar Medical College and Hospital, Kolkata, West Bengal. The study includes short term (5min) HRV analysis in COPD patients between the age group 18years and 60years after fullling appropriate inclusion and exclusion criteria and the results were analyzed using proper statistical software. After analysis of different data it was found that there is decrease in heart rate variability (in both Time domain and Frequency domain analysis) in case of COPD and also the decrease is more in case of increasing severity grading of COPD. Sympathetic activity increases and vagal or parasympathetic activity upon heart rate decreases with the increase in COPD grading. Further studies with more number of subjects will be helpful in assessing pathophysiology and management of COPD patients with the help of HRV analysis.

Early Left Ventricular Diastolic Dysfunction, Reduced Baroreflex Sensitivity, and Cardiac Autonomic Imbalance in Anabolic-Androgenic Steroid Users.

The effects of androgen anabolic steroids (AAS) use on athletes’ cardiac autonomic activity in terms of baroreflex sensitivity (BRS), and heart rate variability (HRV) have not yet been adequately studied. Furthermore, there is no information to describe the possible relationship between the structural and functional cardiac remodeling and the cardiac autonomic nervous system changes caused by AAS abuse. Thus, we aimed to study the effects of long-term AAS abuse on cardiac autonomic efficacy and cardiac adaptations in strength-trained athletes. In total, 80 strength-trained athletes (weightlifters and bodybuilders) participated in the study. Notably, 40 of them using AAS according to their state formed group A, 40 nonuser strength-trained athletes comprised group B, and 40 healthy nonathletes (group C) were used as controls. All subjects underwent a head-up tilt test using the 30 min protocol to evaluate the baroreflex sensitivity and short HRV modulation. Furthermore, all athletes undertook standard echocardiography, a cardiac tissue Doppler imaging (TDI) study, and a maximal spiroergometric test on a treadmill to estimate their maximum oxygen consumption (VO2max). The tilt test results showed that group A presented a significantly lower BRS and baroreflex effectiveness index than group B by 13.8% and 10.7%, respectively (p < 0.05). Regarding short-term HRV analysis, a significant increase was observed in sympathetic activity in AAS users. Moreover, athletes of group A showed increased left ventricular (LV) mass index (LVMI) by 8.9% (p < 0.05), compared to group B. However, no difference was found in LV ejection fraction between the groups. TDI measurements indicated that AAS users had decreased septal and lateral peak E’ by 38.0% (p < 0.05) and 32.1% (p < 0.05), respectively, and increased E/E’ by 32.0% (p < 0.05), compared to group B. This LV diastolic function alteration was correlated with the year of AAS abuse. A significant correlation was established between BRS depression and LV diastolic impairment in AAS users. Cardiopulmonary test results showed that AAS users had significantly higher time to exhaustion by 11.0 % (p < 0.05) and VO2max by 15.1% (p < 0.05), compared to controls. A significant correlation was found between VO2max and LVMI in AAS users. The results of the present study indicated that long-term AAS use in strength-trained athletes led to altered cardiovascular autonomic modulations, which were associated with indices of early LV diastolic dysfunction.

Heart Rate Variability Duration: Expanding the Ability of Wearable Technology to Improve Outpatient Monitoring?

Heart rate variability (HRV) evaluates beat-to-beat interval (BBI) differences and is a suggested marker of the autonomic nervous system with diagnostic/monitoring capabilities in mental health; especially parasympathetic measures. The standard duration for short-term HRV analysis ranges from 24 h down to 5-min. However, wearable technology, mainly wrist devices, have large amounts of motion at times resulting in need for shorter duration of monitoring. The objective of this study was to evaluate the correlation between 1 and 5 min segments of continuous HRV data collected simultaneously on the same patient. Subjects wore a patch electrocardiograph (Cardea Solo, Inc.) over a 1–7 day period. For every consecutive hour the patch was worn, we selected a 5-min, artifact-free electrocardiogram segment. HRV metric calculation was performed to the entire 5-min segment and the first 1-min from this same 5-min segment. There were 492 h of electrocardiogram data collected allowing calculation of 492 5 min and 1 min segments. 1 min segments of data showed good correlation to 5 min segments in both time and frequency domains: root mean square of successive difference (RMSSD) (R = 0.92), high frequency component (HF) (R = 0.90), low frequency component (LF) (R = 0.71), and standard deviation of NN intervals (SDNN) (R = 0.63). Mental health research focused on parasympathetic HRV metrics, HF and RMSSD, may be accomplished through smaller time windows of recording, making wearable technology possible for monitoring.