Normal-to-normal Intervals Research Articles

Ultra-short-term stress measurement using RGB camera-based remote photoplethysmography with reduced effects of Individual differences in heart rate.

Stress is linked to health problems, increasing the need for immediate monitoring. Traditional methods like electrocardiograms or contact photoplethysmography require device attachment, causing discomfort, and ultra-short-term stress measurement research remains inadequate. This paper proposes a method for ultra-short-term stress monitoring using remote photoplethysmography (rPPG). Previous predictions of ultra-short-term stress have typically used pulse rate variability (PRV) features derived from time-segmented heart rate data. However, PRV varies at the same stress levels depending on heart rates, necessitating a new method to account for these differences. This study addressed this by segmenting rPPG data based on normal-to-normal intervals (NNIs), converted from peak-to-peak intervals, to predict ultra-short-term stress indices. We used NNI counts corresponding to average durations of 10, 20, and 30s (13, 26, and 39 NNIs) to extract PRV features, predicting the Baevsky stress index through regressors. The Extra Trees Regressor achieved R2 scores of 0.6699 for 13 NNIs, 0.8751 for 26 NNIs, and 0.9358 for 39 NNIs, surpassing the time-segmented approach, which yielded 0.4162, 0.6528, and 0.7943 for 10, 20, and 30-s intervals, respectively. These findings demonstrate that using NNI counts for ultra-short-term stress prediction improves accuracy by accounting for individual bio-signal variations.

Parasympathetic nervous system: A key role in control and mood disorders in patients with asthma

BackgroundPatients with severe asthma often have uncontrolled disease and experience mood disorders, particularly anxiety and depression. The autonomic nervous system (ANS) plays an important role in asthma, mainly through the parasympathetic ANS system (PANS), which favors bronchoconstriction and mental health status. ObjectiveTo evaluate the role of the activation of the PANS in uncontrolled asthma and related mood disorders. MethodsThis was a proof-of-concept cross-sectional study that analyzed demographic and clinical variables reflecting asthma severity and control, lung function, inflammation (from induced sputum), evaluation of quality of life, and the risk for anxiety and depression according to validated questionnaires. The PANS analysis was conducted based on heart rate variability: SD of the difference between consecutive normal-to-normal (NN) intervals (SDNN), root mean square of the successive differences (RMSSD), percentage of consecutive NN intervals (pNN50), total power (TP), and respiratory-related power (Pr). ResultsA total of 30 patients with asthma were grouped according to asthma control and the risk for anxiety and depression; 10 patients with uncontrolled asthma compared with the patients with controlled asthma showed significant differences (P < .05) in SDNN (26.5 [8.2] vs 42.7 [29.7]), RMSSD (14.1 [6.5] vs 24 [20]), pNN50 (0.6 [1.5] vs 6.2 [11.8]), TP (0.0005 [0.00046] vs 0.0014 [0.00085]), and Pr (0.0003 [0.00025] vs 0.0007 [0.00060]) respectively. A total of 13 patients at risk for anxiety and depression compared with the patients without showed reduced values (P < .05) for SDNN (26.5 [7.9] vs 45.6 [31.3]), pNN50 (0.75 [1.4] to 7.12 [12.6]), TP (0.0005 [0.00048] to 0.0012 [0.0008]), and Pr (0.0003 [0.00027] to 0.0008 [0.00062]). ConclusionOur results suggest that PANS activity is depressed in patients with uncontrolled asthma and common mood disorders such as depression and anxiety, and the evaluation of heart rate variability may be a useful means for follow-up of asthma control and related mood disorders.

Data Analysis of Heart Rate Variability and Arrhythmia in Patients with Paroxysmal Atrial Fibrillation.

Atrial fibrillation (AF) is the most common type of arrhythmia. Heart rate variability (HRV) may be associated with AF risk. The aim of this study was to test HRV indices and arrhythmias as predictors of paroxysmal AF based on 24-hour dynamic electrocardiogram recordings of patients. A total of 199 patients with paroxysmal AF (AF group) and 204 elderly volunteers over 60 years old (Control group) who underwent a 24-hour dynamic electrocardiogram from August 2022 to March 2023 were included. Time-domain indices, frequency-domain indices, and arrhythmia data of the two groups were classified and measured. Binary logistic regression analysis was performed on variables with significant differences to identify independent risk factors. A nomogram prediction model was established, and the sum of individual scores of each variable was calculated. Gender, age, body mass index and low-density lipoprotein (LDL) did not differ significantly between AF and Control groups (p > 0.05), whereas significant group differences were found for smoking, hypertension, diabetes, and high-density lipoprotein (HDL) (p < 0.05). The standard deviation of all normal to normal (NN) R-R intervals (SDNN), standard deviation of 5-minute average NN intervals (SDANN), root mean square of successive NN interval differences (rMSSD), 50 ms from the preceding interval (pNN50), low-frequency/high-frequency (LF/HF), LF, premature atrial contractions (PACs), atrial tachycardia (AT), T-wave index, and ST-segment index differed significantly between the two groups. Logistic regression analysis identified rMSSD, PACs, and AT as independent predictors of AF. For each unit increase in rMSSD and PACs, the odds of developing AF increased by 1.0357 and 1.0005 times, respectively. For each unit increase in AT, the odds of developing AF decreased by 0.9976 times. The total score of the nomogram prediction model ranged from 0 to 110. The autonomic nervous system (ANS) plays a pivotal role in the occurrence and development of AF. The individualized nomogram prediction model of AF occurrence contributes to the early identification of high-risk patients with AF.

Vagal predominance correlates with mood state changes of winter-over expeditioners during prolonged Antarctic residence.

Winter-over expeditioners in Antarctica are challenged by various environmental and psycho-social stress factors, which may induce psychophysiological changes. The autonomic nervous system (ANS) plays a crucial role in the adaptation process under stress. However, the relationship between ANS activity and the mood states of expeditioners remains largely unexplored. This study aims to uncover the pattern of ANS adjustment under extreme Antarctic environments and provide new insights into the correlations between ANS activity and mood state changes, which may provide scientific data for medical interventions. Fourteen expeditioners at Zhongshan Station participated in this study. The study was conducted during four representative periods: pre-Antarctica, Antarctica-1 (pre-winter), Antarctica-2 (winter), and Antarctica-3 (summer). The heart rate variability (HRV) of the expeditioners was continuously measured for 24 hours to evaluate ANS activity. Plasma levels of catecholamines were tested by ELISA. Mood states were assessed by the Profile of Mood States (POMS) scale. HRV analysis showed a disturbance of ANS during winter and summer periods. For frequency domain parameters, very low frequency (VLF), low frequency (LF), high frequency (HF), and total power (TP) significantly increased during the second half of the mission. Especially, LF/HF ratio decreased during summer, indicating the predominance of vagal tone. Results of the time domain analysis showed increased heart rate variability during the austral winter and summer. Plasma epinephrine (E) significantly increased during residence in Antarctica. Compared with pre-Antarctica, the vigor, depression, and anger scores of the expeditioners decreased significantly during the austral summer. Notably, the depression score showed a moderate positive correlation with LF/HF, while weak negative correlations with other HRV indicators, including TP, VLF, and LF. Anger score showed a moderate positive correlation with LF/HF and weak negative correlations with the average normal-to-normal (NN) interval, and the root mean square of differences between adjacent RR intervals (RMSSD). Plasma E level weakly correlated with the average NN interval. Prolonged residence in Antarctica increased the ANS activities and shifted the cardiac autonomic modulation towards vagal predominance. The alteration of HRV correlated with mood states and plasma epinephrine levels.

P040 Comparisons of Heart Rate Variability Indices Derived from the Sheet-type Device beneath the Mattress with those from the Electrocardiogram

Abstract Introduction A sheet-type device beneath the mattress was developed for non-invasive monitoring of cardiac rhythm during sleep and in bedridden end-of-life elderly patients, enabling the acquisition of ballistocardiography (BCG) signals. BCG represents minute vibrations in the body associated with cardiac ejection of blood and has recently been utilized to estimate heart rate variability (HRV) indices. This study aimed to compare HRV indices derived from BCG with those obtained from simultaneously measured electrocardiogram (ECG) and assess their agreement. Methods Healthy subjects (14 males, 11 females; age 40.6±12.8 yrs.) were recruited between August 2022 and April 2023. Subjects laid on a bed with the device placed under their pillow, while ECG was recorded for 20 minutes. Time-domain indices (mean normal-to-normal (NN) interval) and frequency-domain indices (low frequency (LF) and high frequency (HF)) were calculated, and linear associations were examined by correlation analysis. Bland-Altman analysis was employed to evaluate the agreement between the indices. Results Significant positive associations were observed between BCG and ECG indices in mean NN interval (r=0.994, p&amp;lt;0.001) and LF (r=0.685, p&amp;lt;0.001) and HF (r=0.687, p&amp;lt;0.001). Bland-Altman analysis demonstrated good agreement in mean NN (mean of pairwise difference (MPD): 1.07; limits of agreement (LA): -12.57-14.70; ratio: 0.01), but poor agreement in LF (MPD: -4.32; LA: -30.42-21.78; ratio: 0.63) and HF (MPD: 4.29; LA: -21.70-30.28; ratio: 0.45) based on the ratios (&amp;gt; 0.2). Conclusion The high correlation and good agreement between mean NN intervals suggest that the BCG device can serve as an alternative to HRV for estimating NN interval.

Clinical Effect Analysis of Small and Medium Doses of Betaloc Combined with Amiodarone in the Treatment of Ventricular Arrhythmia

Objective: To explore and analyze the clinical effect of small and medium doses of Betaloc combined withamiodarone in the treatment of ventricular arrhythmia. Methods: 60 patients with ventricular arrhythmia that were treated in the Department of Cardiology of our hospital from May 2018–May 2023 were selected for this study, and they were divided into a research group (n = 30) and a reference group (n = 30). The study group was treated with small doses of Betaloc and amiodarone, while the reference group was treated with conventional treatment. The total efficacy of medication, QRS interval, standard deviation of normal-to-normal (NN) intervals (SDNN), root mean square of successive differences between normal heartbeats (RMSSD), standard deviation of the average NN intervals (SDANN), and incidence of adverse reactions were compared between the groups. Results: The effectiveness of medication in the study group was significantly higher than that in the reference group (P &lt; 0.05). Besides, there was no statistically significant difference (P &gt; 0.05) in the QRS interval and SDNN between the two groups before treatment. After treatment, the QRS interval and SDNN of the study group were significantly lower than those of the reference group (P &lt; 0.05). Before treatment, there was no significant difference in RMSSD and SDANN between groups (P &gt; 0.05). After treatment, RMSSD and SDANN in the study group were significantly better than those in the reference group (P &lt; 0.05), and the difference was statisticallysignificant. The incidence of adverse reactions in the study group was significantly lower than that in the reference group (P &lt; 0.05), and the difference was statistically significant. Conclusion: Small doses of Betoprolol and amiodarone is more effective in the treatment of ventricular arrhythmia, which has the value of popularization and application.

Changes in Heart Rate after Pulmonary Vein Isolation in Patients with Paroxysmal Atrial Fibrillation and Sinus Bradycardia.

This study aimed to evaluate the effect of circumferential pulmonary vein isolation (CPVI) on autonomic nervous function and prognosis in patients with paroxysmal atrial fibrillation (AF) with or without sinus bradycardia.A total of 66 patients with paroxysmal AF accompanied by sinus bradycardia and who underwent CPVI were recruited as the sinus bradycardia group. A total of 91 patients with paroxysmal AF but without sinus bradycardia and who underwent catheter ablation were selected as the control group. After surgical contraindications were eliminated, CPVI was performed by three-dimensional mapping system. 24-hour dynamic electrocardiogram was used to observe the changes of heart rate before and 2 days after surgery.A total of 45 (68%) and 51 (56%) patients in the sinus bradycardia and control groups, respectively, maintained sinus rhythm. There was an increase in heart rate after CPVI in both groups. The standard deviation of normal-to-normal (NN) intervals (SDNN), standard deviation of the average NN intervals (SDANN), low frequency (LF), and LF/high frequency (HF) in the sinus bradycardia and control groups decreased after CPVI (P < 0.01). Moreover, SDANN was higher in patients with sinus bradycardia treated by successful ablation than in those with recurrence (P < 0.01), while SDNN, a standard statistical measure of heart rate variability (rMSSD), LF, and HF were significantly lower in patients with sinus bradycardia (P < 0.05).CPVI was able to produce a significant reduction effect on vagal nerve and sympathetic activity regardless of whether patients with paroxysmal AF had sinus bradycardia. Moreover, CPVI exerted a certain influence on the success rate of AF catheter ablation.

Oxidative stress associated with impaired autonomic control and severity of lung function in chronic obstructive pulmonary disease patients.

Oxidative stress has been suggested to play a role in the pathogenesis of chronic obstructive pulmonary disease (COPD). This study aimed to investigate a link between malondialdehyde (MDA) levels, pulmonary function, and cardiac autonomic control in patients with COPD. Plasma levels of MDA, heart rate variability, and pulmonary function were measured in 50 clinically stable COPD patients and 50 normal male controls. COPD patients exhibited lower means of the standard deviations of all normal to normal (NN) intervals (SDNN), the square root of the mean of the sum of the squares of differences between adjacent NN intervals (RMSSD), and high frequency (HF). Nevertheless, they presented greater low frequency (LF) and low frequency/high frequency ratio (LF/HF ratio) in supine and head-up tilt positions than controls (P<0.001). More-over, a negative correlation between MDA levels with SDNN (P<0.001) and a positive correlation with LF (P<0.01) and LF/HF ratio (P<0.05) were observed in both positions. In COPD patients, plasma MDA levels were 2.3 times greater than controls (4.33±2.03 μM vs. 1.89±0.39 μM, P<0.001), and they were inversely correlated with forced vital capacity, forced expiratory volume in 1 sec, midexpiratory flow, and peak expiratory flow (P<0.001). Our findings suggest a potential role for oxidative stress in impaired cardiac autonomic control and clinical relevance of plasma MDA levels as a predictor of severity of COPD in COPD patients.

Autonomic dysfunction in COVID-19 patients receiving mechanical ventilation: A cross-sectional study

Coronavirus disease 2019 (COVID-19) can damage cardiac tissue by increasing troponin levels and inducing arrhythmias, myocarditis, and acute coronary syndrome. To analyze the impact of COVID-19 on cardiac autonomic control in mechanically ventilated intensive care unit (ICU) patients. This cross-sectional analytical study of ICU patients of both sexes receiving mechanical ventilation was conducted in a tertiary hospital. Patients were divided into COVID-19-positive (COVID(+)) and COVID-19-negative (COVID(-)) groups. Clinical data were collected and heart rate variability (HRV) records obtained using a heart rate monitor. The study sample comprised 82 subjects: 36 (44%) in the COVID(-) group (58.3% female; median age, 64.5 years) and 46 (56%) in the COVID(+) group (39.1% females; median age, 57.5 years). The HRV indices were lower than the reference values. An intergroup comparison identified no statistically significant differences in the mean normal-to-normal (NN) interval, standard deviation of the NN interval, or root mean square of successive differences in NN intervals. The COVID(+) group had an increased low frequency (P = 0.05), reduced high frequency (P = 0.045), and increased low frequency/high frequency (LF/HF) ratio (P = 0.048). There was a weak positive correlation between LF/HF and length of stay in the COVID(+) group. Patients who received mechanical ventilation had lower overall HRV indices. COVID(+) patients who received mechanical ventilation had lower vagal HRV components. These findings likely indicate clinical applicability, as autonomic control impairments are associated with a greater risk of cardiac death.

Effect of Algorithmic Music Listening on Cardiac Autonomic Nervous System Activity: An Exploratory, Randomized Crossover Study.

It is proven that music listening can have a therapeutic impact in many clinical fields. However, to assume a curative value, musical stimuli should have a therapeutic logic. This study aimed at assessing short-term effects of algorithmic music on cardiac autonomic nervous system activity. Twenty-two healthy subjects underwent a crossover study including random listening to relaxing and activating algorithmic music. Electrocardiogram (ECG) and non-invasive arterial blood pressure were continuously recorded and were later analyzed to measure Heart Rate (HR) mean, HR variability and baroreflex sensitivity (BRS). Statistical analysis was performed using a general linear model, testing for carryover, period and treatment effects. Relaxing tracks decreased HR and increased root mean square of successive squared differences of normal-to-normal (NN) intervals, proportion of interval differences of successive NN intervals greater than 50 ms, low-frequency (LF) and high-frequency (HF) power and BRS. Activating tracks caused almost no change or an opposite effect in the same variables. The difference between the effects of the two stimuli was statistically significant in all these variables. No difference was found in the standard deviation of normal-to-normal RR intervals, LFpower in normalized units and LFpower/HFpower variables. The study suggests that algorithmic relaxing music increases cardiac vagal modulation and tone. These results open interesting perspectives in various clinical areas.

Ecg Features of Cardiac Autonomic Neuropathy In Patients With Type 2 Diabetes Mellitus

IntroductionCardiac autonomic neuropathy (CAD) is associated with a poor cardiac prognosis, particularly with an increased risk of sudden death in diabetic patients. A lengthening of the QT interval and alteration of the QT dispersion have been reported in patients with diabetic CAD as well as increased sympathetic activity confirmed by the heart rate variability (HRV) assessment. Material and MethodsWe conducted a randomized study: 77 patients were enrolled in the Sumy Region Affair Hospital, among them 46 had type 2 diabetes mellitus (DM) for 5 years and longer (group A), 31 had normal glucose profile, history of DM was absent (group B). Our patients have been subjected to physical examination, blood tests (glucose, HbA1c, lipid profile), 12-lead ECG with HRV measure. The authors had full access and take responsibility for the integrity of the data. ResultsIt was detected that in patients with DM QTc interval values were close to the upper limits (461.5±26.61ms). The QTc averages of normal-to-normal (NN) intervals (SDANN), root mean square differences of successive NN intervals (RMSSD) and low-frequency (LF) – high-frequency (HF) power ratio were significantly higher in patients with DM (p<0.05). LF/HF was statistically linked to the increase of HbA1c and decrease of magnesium level. It was detected that changes could be improved by the glucose level control and treatment with magnesium supplements 100 mg per day for 30 days (p<0.05). ConclusionCAD is associated with QT prolongation and HRV disturbances. Further research of possible long-term consequences and approaches to their correction is required.

Cardiac Arrhythmias and Impaired Heart Rate Variability in Older Patients With Ventricular Septal Defects.

BackgroundCongenital ventricular septal defects (VSDs) are considered to have benign long‐term outcome when treated correctly in childhood. However, abnormal parameters are described in younger adults, including impaired heart rate variability (HRV). It is not known whether such abnormalities will deteriorate with age. Therefore, HRV and cardiac events, such as premature ventricular contraction, were evaluated in patients aged >40 years with congenital VSDs and compared with healthy peers.Methods and ResultsA total of 30 surgically closed VSDs (51±8 years, repair at median age 6.3 years with total range 1.4–54 years) with 30 healthy controls (52±9 years) and 30 small, unrepaired VSDs (55±12 years) with 30 controls (55±10 years) were all equipped with a Holter monitor for 24 hours. Compared with healthy peers, surgically closed patients had lower SD of the normal‐to‐normal (NN) interbeat interval (129±37 versus 168±38 ms; P<0.01), SD of the average NN intervals for each 5‐minute segment of a 24‐hour HRV recording (116±35 versus 149±35 ms; P<0.01) and 24‐hour triangular index (31±9 versus 44±11; P<0.01). SD of the NN intervals, SD of the average NN intervals for each 5‐minute segment of a 24‐hour HRV recording, and triangular index were comparable between unrepaired VSDs and healthy peers. SD of the NN intervals was <100 ms in 22% of surgically closed and 10% of unrepaired VSDs, whereas controls were within normal ranges. A high number of premature ventricular contractions (>200 events) was registered in 57% of surgical patients compared with 3% of controls (P<0.01), and 53% of unrepaired VSDs compared with 10% in controls (P<0.01).ConclusionsAdults aged >40 with congenital VSDs demonstrate impaired HRV, mainly among surgically closed VSDs. More than half demonstrated a high number of premature ventricular contractions. These novel findings could indicate long‐term cardiovascular disturbances. This necessitates continuous follow‐up of VSDs throughout adulthood.

Association Between Postoperative Long-Term Heart Rate Variability and Postoperative Delirium in Elderly Patients Undergoing Orthopedic Surgery: A Prospective Cohort Study.

BackgroundPostoperative delirium (POD) is a common complication after orthopedic surgery in elderly patients. The elderly may experience drastic changes in autonomic nervous system (ANS) activity and circadian rhythm disorders after surgery. Therefore, we intend to explore the relationship between postoperative long-term heart rate (HR) variability (HRV), as a measure of ANS activity and circadian rhythm, and occurrence of POD in elderly patients.MethodsThe study population of this cohort was elderly patients over 60 years of age who scheduled for orthopedic surgery under spinal anesthesia. Patients were screened for inclusion and exclusion criteria before surgery. Then, participants were invited to wear a Holter monitor on the first postoperative day to collect 24-h electrocardiographic (ECG) data. Parameters in the time domain [the standard deviation of the normal-to-normal (NN) intervals (SDNN), mean of the standard deviations of all the NN intervals for each 5-min segment of a 24-h HRV recording (SDNNI), and the root mean square of successive differences of the NN intervals (RMSSD)] and frequency domain [heart rate (HR), high frequency (HF), low frequency (LF), very low frequency (VLF), ultra low frequency (ULF), and total power (TP)] were calculated. Assessment of delirium was performed daily up to the seventh postoperative day using the Chinese version of the 3-Min Diagnostic Interview for CAM-defined Delirium (3D-CAM). The relationship between HRV and POD, as well as the association between HRV and duration of POD, was assessed.ResultsOf the 294 cases that finally completed the follow-up, 60 cases developed POD. Among the HRV parameters, SDNNI, VLF, and ULF were related to the occurrence of POD. After adjustment for potential confounders, the correlation between HRV indices and POD disappeared. Through stratified analysis, two significant negative correlations emerged: ULF in young-old participants and SDNNI, VLF, and ULF in male patients.ConclusionThe lower HRV parameters may be related to the occurrence of POD, and this correlation is more significant in young-old and male patients. ANS disorders and rhythm abnormalities reflected by HRV changes may represent a possible mechanism that promotes POD.

HRV Features as Viable Physiological Markers for Stress Detection Using Wearable Devices.

Stress has been identified as one of the major causes of automobile crashes which then lead to high rates of fatalities and injuries each year. Stress can be measured via physiological measurements and in this study the focus will be based on the features that can be extracted by common wearable devices. Hence, the study will be mainly focusing on heart rate variability (HRV). This study is aimed at investigating the role of HRV-derived features as stress markers. This is achieved by developing a good predictive model that can accurately classify stress levels from ECG-derived HRV features, obtained from automobile drivers, by testing different machine learning methodologies such as K-Nearest Neighbor (KNN), Support Vector Machines (SVM), Multilayer Perceptron (MLP), Random Forest (RF) and Gradient Boosting (GB). Moreover, the models obtained with highest predictive power will be used as reference for the development of a machine learning model that would be used to classify stress from HRV features derived from heart rate measurements obtained from wearable devices. We demonstrate that HRV features constitute good markers for stress detection as the best machine learning model developed achieved a Recall of 80%. Furthermore, this study indicates that HRV metrics such as the Average of normal-to-normal (NN) intervals (AVNN), Standard deviation of the average NN intervals (SDNN) and the Root mean square differences of successive NN intervals (RMSSD) were important features for stress detection. The proposed method can be also used on all applications in which is important to monitor the stress levels in a non-invasive manner, e.g., in physical rehabilitation, anxiety relief or mental wellbeing.

Elevated circulating growth differentiation factor 15 is related to decreased heart rate variability in chronic kidney disease patients

Background Growth differentiation factor 15(GDF15) is a distant member of the superfamily of the transforming growth factor beta (TGF-β). It has been established that increased GDF15 levels are associated with an increased risk of cardiovascular disease. However, the detail effect of GDF15 on cardiovascular system in patients with chronic kidney disease (CKD) needs detail analysis. Methods Patients with CKD who did not need dialysis were enrolled in the study. Blood pressure (BP), endothelial function, pulse wave velocity (PWV) and heart rate variability (HRV) were taken in all subjects. Plasma GDF15 concentration was measured by an enzyme-linked immunosorbent assay. Results Among the 355 participants, the mean age was 57.4 (±14.2) years old and the mean estimated glomerular filtration rate (eGFR) was 50.1 (±33.2) mL/min/1.73m2. The average plasma GDF15 level was 1394.7 (±610.1) pg/mL. Higher GDF15 concentrations were significantly associated with decreased eGFR and increased urine protein-to-creatinine ratio (uPCR). In multivariable models, after adjusting for potential confounders, plasma GDF15 has negative concerning with HRV parameters including the standard deviation of the normal-to-normal (NN) interval (SDNN), the square root of the mean of the sum of the squares of differences between adjacent NN intervals (RMSSD) and Triangular Index. Conclusion We observed there was a link between increased plasma of GDF15 and decreased HRV. The mechanisms and prediction of GDF15 in the cardiovascular disease with CKD needs further discussion and study.

The Impact of Remote Ischaemic Conditioning on Beat-to-Beat Heart Rate Variability Circadian Rhythm in Healthy Adults

Remote ischaemic conditioning (RIC) is an intervention that may exert a protective effect over multiple tissues or organs by regulating neuronal signal transduction. Heart rate variability (HRV) can assess the state of the autonomic nervous system. However, whether RIC can also regulate HRV in humans remains unknown. This was a self-controlled interventional study in which serial beat-to-beat monitoring was performed at the same seven time points (7, 9, and 11 AM; 2, 5, and 8 PM; and 8 AM on the next day) with or without RIC in 50 healthy adults. The seven time points on the RIC day were defined as baseline, 1 hour, 3 hours, 6 hours, 9hours, 12 hours, and 24 hours after RIC. The RIC protocol consisted of 4×5-minute inflation/deflation in one arm and one thigh cuff at 200 mmHg pressure from 7:20 to 8 AM. This study is registered on ClinicalTrials.gov (NCT02965547). We included 50 healthy adult volunteers (aged 34.54±12.01 years, 22 men [44%], all Asian). The variables analysed in frequency-domain measures performed as power of low-frequency in normalised units (0.04-0.15 Hz), high-frequency in normalised units (0.15-0.40 Hz), and ratio of low frequency to high frequency. The time-domain parameters standard deviation (SD) of all normal to normal (NN) intervals (SDNN), mean of the 5-minute SD of the NN intervals, SD of the consecutive 5-minute averages of NN intervals, and the root mean square of successive differences of NN intervals, and time-domain parameters calculated from Poincaré plots, SD of the short diagonal axis in Poincaré plot (SD1), SD of the long diagonal axis in Poincaré plot (SD2), and SD1/SD2 were also obtained. The SDNN and SD2 significantly increased 1 hour after RIC (p=0.029 and p=0.045, respectively). Additionally, the SD2 increased a second time 12 hours after RIC (p=0.041), which represented inhibited sympathetic activity. Heart rate variability increase and sympathetic inhibition induced by RIC appeared both on the early and delayed protective window of RIC, which may indicate some of the underlying mechanisms by which RIC may offer protection.

Autonomic Influences Related to Early Repolarization in Patients Without Structural Heart Disease

This cross-sectional study focused on the association between heart rate variability (HRV) and early repolarization pattern (ERP). It included 1236 patients categorized into three groups: ERP type 1: J-point elevation with notched/slurred QRS; ERP type 2: ST elevation without dominant J-wave; and non-ERP group. Analyzing time-domain indexes include standard deviation of NN (normal-to-normal) RR intervals (SDNN), root mean square of successive difference in NN RR intervals (RMSSD), and proportion of consecutive NN intervals that differ by more than 50ms (PNN50), there were significant differences between any two groups (all P < 0.01). All time-domain indexes showed: ERP type 2 > ERP type 1 > non-ERP. Multivariate logistic regression analysis revealed that SDNN at nighttime and gender were independently associated with the maximum magnitude of J-point elevation ≧0.2mV. The findings strongly suggested that based on electrocardiogram characteristics, parasympathetic tone denoted by HRV may be related to different types of ERP.

Emotion Recognition Using Convolutional Neural Network with Selected Statistical Photoplethysmogram Features

Emotion recognition research has been conducted using various physiological signals. In this paper, we propose an efficient photoplethysmogram-based method that fuses the deep features extracted by two deep convolutional neural networks and the statistical features selected by Pearson’s correlation technique. A photoplethysmogram (PPG) signal can be easily obtained through many devices, and the procedure for recording this signal is simpler than that for other physiological signals. The normal-to-normal (NN) interval values of heart rate variability (HRV) were utilized to extract the time domain features, and the normalized PPG signal was used to acquire the frequency domain features. Then, we selected features that correlated highly with an emotion through Pearson’s correlation. These statistical features were fused with deep-learning features extracted from a convolutional neural network (CNN). The PPG signal and the NN interval were used as the inputs of the CNN to extract the features, and the total concatenated features were utilized to classify the valence and the arousal, which are the basic parameters of emotion. The Database for Emotion Analysis using Physiological signals (DEAP) was chosen for the experiment, and the results demonstrated that the proposed method achieved a noticeable performance with a short recognition interval.

Heart Rate Variability during Heat Exposure is not Affected by Short‐term Passive Heat Acclimation in Young Healthy Participants

INTRODUCTIONHeat acclimation attenuates the increase in heart rate during heat exposure. This heat acclimation‐induced bradycardia has been associated with increased stroke volume due to blood volume expansion. However, exercise‐induced heat acclimation also modulates cardiac parasympathetic activity, as measured through heart rate variability (HRV). Therefore, it is possible that modulation of cardiac autonomic activity could contribute to the effect of heat acclimation on heart rate during heat exposure. The purpose of this study was to determine if HRV during heat exposure is modified by short‐term passive heat acclimation.METHODSFifteen healthy adults (27 ± 5 years, 5 females/10 males) underwent heat exposure in a water‐perfused suit to increase esophageal temperature (Tes) by 1.2°C, before and after a 7‐day controlled hyperthermia protocol. During heat exposure, R‐R interval was measured continuously with a 5‐lead electrocardiogram and used to calculate heart rate (HR), mean normal‐to‐normal intervals (NN), standard deviation of NN intervals (SDNN), root mean square of successive NN interval differences (RMSSD), low‐frequency (LF) and high‐frequency spectral power (HF) and the LF‐to‐HF power ratio (LF/HF). The acclimation protocol consisted of hot water immersion to elevate and subsequently maintain rectal temperature ≥38.6°C for 60 minutes once a day for 7 consecutive days. Variables were compared between the pre and post acclimation visit at baseline and at increases in Tes of 0.6°C and 1.2°C.RESULTSHeat acclimation lowered resting Tes (36.81 ± 0.29 to 36.53 ± 0.32°C, P&lt;0.001) and, consequently absolute Tes during heat exposure. When analyzed as a function of the change in Tes from baseline, no difference was observed for HR (P=0.072) at baseline (59 ± 10 vs. 57 ± 9 bpm), +0.6°C (88 ± 12 vs. 86 ± 11 bpm), and +1.2°C (103 ± 13 to 99 ± 12 bpm). Similarly, NN (baseline: 1049 ± 172 vs. 1081 ± 162 ms, +0.6°C: 691 ± 104 vs. 705 ± 100 ms, +1.2°C: 595 ± 74 vs. 600 ± 96 ms, P=0.295), SDNN (baseline: 84 ± 38 vs. 90 ± 37 ms, +0.6°C: 43 ± 15 vs. 45 ± 15 ms, +1.2°C: 28 ± 9 vs. 31 ± 8 ms, P=0.294) and RMSSD (baseline: 83 ± 49 vs. 93 ± 57 ms, +0.6°C: 19 ± 9 vs. 19 ± 14 ms, +1.2°C: 9 ± 4 vs. 9 ± 3 ms, P=0.336) did not differ after heat acclimation. No effect of heat acclimation was also observed for LF (P=0.339), HF (P=0.509) and LF/HF ratio (P=0.449).CONCLUSIONSThese results suggest that short‐term, passive and isothermic heat acclimation does not modulate cardiac autonomic activity during passive heat exposure in healthy young adults.Support or Funding InformationNatural Sciences and Engineering Research Council of Canada, Canada Foundation for Innovation and Montreal Heart Institute Foundation.

Happiness at Your Fingertips: Assessing Mental Health with Smartphone Photoplethysmogram-Based Heart Rate Variability Analysis.

Background: Heart rate variability (HRV) provides essential mental health information for clinical diagnosis, telemedicine, preventive medicine, and public health; however, the lack of a convenient detection method limits its potential. Objective: This study aims to investigate the feasibility and credibility of smartphone photoplethysmogram (PPG)-based HRV analysis for mental well-being and health assessment. Methods: Data were collected from 93 students and university employees in Shenzhen, China. Forty-six percent were male, and the average age was 23.71 years (σ = 4.33). An app recorded a 4-min video of their fingertips and converted the frames into five HRV measures, including the root mean square of successive differences (rMSSD), standard deviation of the normal-to-normal (NN) intervals (SDNN), percentage of successive NN intervals differing by ≥50 ms (pNN50), log high-frequency (HF) HRV, and log low-frequency (LF) HRV. Results: The data verify the positive relationship between mental well-being and HRV measures. Participants with higher Satisfaction With Life Scale (SWLS) scores have a higher rMSSD (p = 0.047), SDNN (p = 0.009), log HF (p = 0.02), and log LF (p = 0.003). Participants who suffer from depression have lower log HF (p = 0.048) and log LF (p = 0.02). Participants in the high-anxiety group have lower pNN50 (p = 0.04) and log HF (p = 0.03). Conclusions: The results of this study validate the feasibility of using the smartphone PPG by demonstrating similar results to previous findings. Our data also support the theorized positive link between mental health and HRV.