Nonlinear Heart Rate Variability Research Articles

Cardiovascular responses as predictors of mortality in children with acute brain injury.

Investigate the utility of cardiovascular responses such as heart rate (HR), blood pressure (BP), and heart rate variability (HRV) in the prognosis of children with acute acquired brain injury (ABI). Children under 18 years with severe acute acquired brain injury (ABI) who survived at least 12 h after PICU admission were included in a prospective observational cohort in a tertiary academic PICU. Physiological variables, neurological data, laboratory tests (chemistry and hematology), and medications were recorded within 12 h of admission. Linear and nonlinear HRV indices, CT scans, PICU scores, and survival rates were evaluated. Seventy-two children, median age 10.7 years (IQR 4.1-13.6), were eligible for the study; 28 (38.9%) were diagnosed with brain death (BD). Tachycardia, SBP and MBP < 5th percentile, and MBP and DBP> 99th percentile were significantly associated with mortality. Poincaré SD1/SD2 was significantly associated with mortality after adjusting for age, sex and ongoing medication. Tachycardia, systolic hypotension and median hypo and hypertension were associated to mortality in children with severe ABI. While further validation through larger, multicenter studies is necessary, the Poincaré SD1/SD2 ratio has shown promise as a prognostic tool for predicting mortality in children with severe ABI. This study explores cardiovascular changes, including heart rate and blood pressure, and linear/nonlinear HRV measures using ECG at 1000 Hz, and compare them with other prognostic factors like brain tomography and PICU scores. Tachycardia, hypo/hypertension in the early hours after admission are linked to early mortality in children with severe traumatic and non-traumatic brain injury. Linear/non-linear measures of HRV were also related to survival. Higher HRV values indicating better survival chances. We identified Poincaré SD1/SD2 ratio as a promising tool for predicting mortality in children with severe ABI.

HD-MVCNN: High-density ECG signal based diabetic prediction and classification using multi-view convolutional neural network

Diabetes mellitus, also known as diabetes, is a medical condition marked by high blood sugar levels and impacts a large population worldwide. Treating diabetes is not feasible. It can be managed. Hence, it is crucial to promptly identify a diagnosis of diabetes. This study explores the effects of diabetes on the heart, focusing on heart rate variability (HRV) signals, which can offer valuable information about the existence and seriousness of diabetes through the evaluation of diabetes-related heart problems. Extracting crucial data from the irregular and nonlinear HRV signal can be quite challenging. Studying cardiac diagnostics involves a thorough analysis of electrocardiogram (ECG) signals. Traditional electrocardiogram recordings utilize twelve channels, each capturing a complex combination of activities originating from different regions of the heart. Examining ECG signals recorded on the body’s surface may not be an effective method for studying and diagnosing diabetic issues. The study introduces a research proposal utilizing a high-density resolution electrocardiogram (ECG) system with a minimum of 64 channels and multi-view convolutional neural network classification (HD-MVCNN) to address the mentioned challenges. This framework may help identify the hypoglycaemia effects on brain regions, leading to decreased complexity and increased theta and delta power during scalp electrocardiogram procedures. The convolutional architectural model primarily contributes to enhancement and optimization through its Stochastic Gradient Descent (SGD) along with convolutional layers and according to results, the HD-MVCNN demonstrated better stability and accuracy in comparison to traditional classification models. Thus, HD-MVCNN shows promise as a powerful method for classifying features in diabetes clinical data.

Synthetic assessment of cardiac autonomic modulation and Baevsky stress index in patients with synucleinopathies

Abstract Background The Baevsky Stress Index (BSTRi), calculated from Heart Rate Variability (HRV) data, has been proposed for quantitative assessment of physiological stress, with higher scores indicating higher levels of physical and/or psychological stress [1]. Cardiac autonomic modulation can be synthetically quantified by calculating the parasympathetic (PNSi) and the sympathetic (SNSi) indexes. The values of the BSTRi, SNSi, and PNSi in patients with synucleinopathies of different prognoses have not been reported yet. Purpose To quantify, in patients with Parkinson's disease (PD) and Multisystem Atrophy (MSA), the BSTRi, its correlation with the PNSi and the SNSi indexes, and their potential value for a synthetic assessment of cardiac autonomic modulation and early differential diagnosis between PD and MSA. Methods Holter ECG data of 66 patients with Parkinsonian syndromes were retrospectively analyzed after 10 years of follow-up. Out of them, 34 patients with a certain diagnosis of PD (17) and MSA (17) were selected for this study. HRV was analyzed with the Kubios software (version 4.0), providing automatic calculation of the BSTRi, PNSi, and SNSi [2], as well as of time domain (TD), frequency domain (FD), nonlinear (NL), and time-varying (TV) HRV parameters. HRV was calculated from selected short-term intervals (of 5 minutes), during daily activity (ACT5’), and non-REM sleep (NREM5’), and from 24-hours Holter recordings. Patients’ HRV findings were compared with those of 51 age-matched healthy subjects (HS). Results An example of individual automatic graphic summary is shown in Figure 1. Both short-term and 24-hour BSTRi and SNSi values were significantly (p &amp;lt; 0.05) higher in PD and MSA compared to those of HS, in all investigated conditions. Short-term PNSi was significantly higher in HS than in PD in all conditions, but only during NREM5’ in MSA patients (Table 1). No significant difference was found between the indexes of PD and MSA patients. As in HS (R=92), BSTRi was positively correlated with the SNSi in MSA (average R= 0.83 and 0.89 during ACT5’ and NREM5’, respectively), but less evident in PD (R=0.67). The inverse correlation between PNSi and SNSi (R=0.75 in HS) was lost in both MSA and PD. Conclusions Higher values of BSTRi in PD and MSA compared to HS suggest that patients with synucleinopathies do experience higher levels of psychophysiological stress, which may affect their quality of life negatively. However, since no significant difference was found in this study between BSTRi values of PD and MSA patients, BSTRi seems at present unreliable for early differentiation between the two diseases. Telematic assessment of BSTRi, SNSi, and PNSi could be useful for remote monitoring of PD and MSA patients’ psychophysiological stress, to provide timely intervention and adaptive treatment.Fig.1 Example of graphic summary (ACT5')

Heart rate variability and insomnia in depressed patients with breast cancer

ObjectivesDepression is associated with unhealthy autonomic regulation. However, whether patients with breast cancer (BC) with different degrees of depression can be identified from linear and non-linear dynamics in the autonomic...

Comprehensive linear and nonlinear heart rate variability normative data in children.

The autonomic nervous system (ANS) is critical in regulating involuntary bodily functions, including heart rate. Heart rate variability (HRV) reflects the complex interplay between the ANS and humoral factors, making it a valuable noninvasive tool for assessing autonomic function. While HRV has been extensively studied in adults, normative data for HRV in children, primarily based on long-term rhythm recordings, are limited. This study aimed to establish comprehensive normative data for HRV in children. In this retrospective study, we examined 24-h Holter monitors of children aged 1day to 18years, divided into six age groups, at Nemours Children's Health in Orlando, Florida, spanning the years 2013-2023. HRV analysis encompassed time-domain, frequency-domain, and nonlinear indices. Holter data for a total of 247 patients in six age groups were included. An age-related uptrend was observed in all time- and frequency-domain variables except the normalized unit of low-frequency power. Entropy analysis revealed contradictory results among different entropy techniques. Sample and approximate entropy analyses were consistent and showed less complexity and more predictability of HRV with decreasing heart rate, while Shannon entropy analysis showed the opposite. Fractal detrended fluctuation analysis exhibited significant decreases across the age groups, suggestive of diminishing self-similarity of HRV patterns. Control of heart rate and HRV is a highly complex process and requires further study for a better understanding. It seems that no single parameter can fully elucidate the entire process. A combination of time-domain, frequency-domain, and nonlinear indices may be necessary to explain HRV behavior in the growing body.

Heart Rate Variability in Military Pilots During Flight: A Scoping Review.

Piloting an aircraft is a complex multitasking activity that involves managing information in a nonautomatic way and generates a high workload (psychological, cognitive, and physical) for the pilot. The excess of these demands can result in decreased performance and may impair flight safety. Heart rate variability (HRV) has been used in recent studies as a method to investigate operator's workload in complex environments. This measure can assess the stress and recovery ability of the autonomic nervous system. However, a better understanding of flight influence on the pilot's autonomic modulation is necessary. Therefore, this scoping review aims to systematically map the studies related to changes in the autonomic modulation in military pilots during flight, in order to characterize their workload at different times and flight profiles. A literature search was conducted using MEDLINE (by PubMed), SCOPUS, and LILACS databases. Recent records (2002-2022) that analyzed HRV in military pilots during flight were included. Meanwhile, studies in which piloting activity was not performed were excluded. The study was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline extension for Scoping Reviews and the Updated Methodological Guidance for the Conduct of Scoping Reviews. A total of 298 records were obtained, of which 19 were included in the scoping review. The studies analyzed flights performed in high- and low-performance aircrafts, helicopters, and flight simulators, using time domain, frequency domain, and nonlinear HRV indices. Real and simulated flights produced significant autonomic changes. Some flights elicited autonomic nervous system responses that persisted up to 5 h after landing. During real flight, the most sensitive indices for identifying variations in pilot workload were root mean square of successive differences between normal heartbeats, standard deviation of interbeat interval of normal sinus beat (SDNN), ratio of low-frequency to high-frequency power, and Poincaré plot standard deviation perpendicular to the line of identity (SD1), whereas the interbeat interval (RR), SDNN, SD1, and Poincaré plot standard deviation along the line of identity (SD2) were the most sensitive indices when comparing segments of simulated flight with different levels of difficulty. This scoping review provided insight into the influence of flight on autonomic modulation in military pilots. Some key themes were highlighted: Increased sympathetic activity during flight, sensibility of different domains of HRV to flight demands, and autonomic changes during recovery time. Future research efforts may allow us to enhance the understanding of pilot's workload limits and to elucidate the optimal postflight recovery time.

Affective Implications of Human-Animal Relationship on Pig Welfare: Integrating Non-Linear Heart Rate Variability Measures.

The human-animal relationship is crucial for animal welfare. Gentle handling enhances pigs' comfort while rough handling causes fear and stress. This study examined how different human-animal relationship qualities affect the behavior and heart rate variability (linear and non-linear parameters) of 36 nursery pigs. Over six weeks, pigs experienced positive (n = 12), minimal (n = 12), or negative (n = 12) human handling. Their responses to handlers were then assessed in an experimental arena with four phases: habituation, exposure to the handler standing and sitting, and forced interaction. Pigs subjected to negative handling exhibited increased fear-related behaviors, spending less time in contact with the handler. They also exhibited heightened stress responses, with greater LF/HF ratio and Lmean values compared with positively handled pigs. Conversely, gently handled pigs displayed affiliative behaviors, accepting more strokes, and higher parasympathetic activation, indicated by greater RMSSD/SDNN and SampEn values, suggesting a more positive affective state. Minimally handled pigs exhibited some behavioral similarities to gently handled pigs, although physiological data indicated that the interaction was likely more rewarding for the gently handled pigs. These results emphasize the impact of human-animal relationships on pig welfare and highlight the value of incorporating non-linear heart rate variability parameters in such evaluations.

Relationship of Cycling Power and Non-Linear Heart Rate Variability from Everyday Workout Data: Potential for Intensity Zone Estimation and Monitoring.

The short-term scaling exponent alpha1 of detrended fluctuation analysis (DFA-a1) of heart rate variability (HRV) has been shown to be a sensitive marker for assessing global organismic demands. The wide dynamic range within the exercise intensity spectrum and the relationship to established physiologic threshold boundaries potentially allow in-field use and also open opportunities to provide real-time feedback. The present study expands the idea of using everyday workout data from the AI Endurance app to obtain the relationship between cycling power and DFA-a1. Collected data were imported between September 2021 and August 2023 with an initial pool of 3123 workouts across 21 male users. The aim of this analysis was to further apply a new method of implementing workout group data considering representative values of DFA-a1 segmentation compared to single workout data and including all data points to enhance the validity of the internal-to-external load relationship. The present data demonstrate a universal relationship between cycling power and DFA-a1 from everyday workout data that potentially allows accessible and regular tracking of intensity zone demarcation information. The analysis highlights the superior efficacy of the representative-based approach of included data in most cases. Validation data of the performance level and the up-to-date relationship are still pending.

Increased stress burden and electrodermal reactivity in bladder cancer patients in comparison to healthy controls

The purpose of our study was to assess specific physiological parameters associated with stress responses in bladder cancer (BCa) patients compared to healthy individuals. By examining the transition from a supine to a sitting position, representing a mild physiological load, we investigated the changes in autonomic nervous system (ANS) activity as reflected by alterations in these parameters, indicating shifts in ANS regulation, using non-linear heart rate variability (HRV) parameters (0V%, 2UV%, parasympathetic and sympathetic nervous system – PNS and SNS indices), modified heart rate acceleration (ACmod) and deceleration capacities (DCmod), heart rate (HR), electrodermal activity (EDA), and also their correlations with perceived stress score. Our findings showed that BCa patients (n = 38) exhibited elevated resting HR, heightened SNS index, and increased EDA compared to their healthy counterparts (n = 47), indicating a notable physiological stress burden. The 0V% parameter showed a positive association with the SNS index, ACmod, HR, and EDA parameters, while displaying a negative correlation with the PNS index, DCmod and 2UV%. These non-linear HRV parameters, such as 0V% and 2UV%, offer nuanced insights into the complexities of heartbeat dynamics and autonomic regulation. After the transition from supine to sitting positions, BCa patients displayed higher EDA responses, indicating heightened stress reactivity and ANS sensitivity. These physiological distinctions persisted even when we did not prove differences in the levels of perceived stress between the studied groups. In conclusion, our study emphasizes the significance of identifying cancer patients at risk of ANS dysregulation, paving the way for tailored stress management strategies.

Biofeedback of elderly patients with chronic pain: new nonlinear Heart Rate Variability analysis

Biofeedback of elderly patients with chronic pain: new nonlinear Heart Rate Variability analysis

Heart rate variability for neuro-prognostication after CA: Insight from the Parisian registry

BackgroundHypoxic ischemic brain injury (HIBI) induced by cardiac arrest (CA) seems to predominate in cortical areas and to a lesser extent in the brainstem. These regions play key roles in modulating the activity of the autonomic nervous system (ANS), that can be assessed through analyses of heart rate variability (HRV). The objective was to evaluate the prognostic value of various HRV parameters to predict neurological outcome after CA. MethodsRetrospective monocentric study assessing the prognostic value of HRV markers and their association with HIBI severity. Patients admitted for CA who underwent EEG for persistent coma after CA were included. HRV markers were computed from 5 min signal of the ECG lead of the EEG recording. HRV indices were calculated in the time-, frequency-, and non-linear domains. Frequency-domain analyses differentiated very low frequency (VLF 0.003–0.04 Hz), low frequency (LF 0.04–0.15 Hz), high frequency (HF 0.15–0.4 Hz), and LF/HF ratio. HRV indices were compared to other prognostic markers: pupillary light reflex, EEG, N20 on somatosensory evoked potentials (SSEP) and biomarkers (neuron specific enolase-NSE). Neurological outcome at 3 months was defined as unfavorable in case of best CPC 3–4-5. ResultsBetween 2007 and 2021, 199 patients were included. Patients were predominantly male (64%), with a median age of 60 [48.9–71.7] years. 76% were out-of-hospital CA, and 30% had an initial shockable rhythm. Neurological outcome was unfavorable in 73%. Compared to poor outcome, patients with a good outcome had higher VLF (0.21 vs 0.09 ms2/Hz, p < 0.01), LF (0.07 vs 0.04 ms2/Hz, p = 0.003), and higher LF/HF ratio (2.01 vs 1.01, p = 0.008). Several non-linear domain indices were also higher in the good outcome group, such as SD2 (15.1 vs 10.2, p = 0.016) and DFA α1 (1.03 vs 0.78, p = 0.002). These indices also differed depending on the severity of EEG pattern and abolition of pupillary light reflex. These time–frequency and non-linear domains HRV parameters were predictive of poor neurological outcome, with high specificity despite a low sensitivity. ConclusionIn comatose patients after CA, some HRV markers appear to be associated with unfavorable outcome, EEG severity and PLR abolition, although the sensitivity of these HRV markers remains limited.

Predominant cardiac sympathetic modulation during wake and sleep in patients with Rett syndrome

BackgroundRett syndrome (RTT) is a rare neurological disorder primarily associated with mutations in the methyl-CpG-binding protein 2 (MECP2) gene. The syndrome is characterized by cognitive, social, and physical impairments, as well as sleep disorders and epilepsy. Notably, dysfunction of the autonomic nervous system is a key feature of the syndrome. Although Heart Rate Variability (HRV) has been used to investigate autonomic nervous system dysfunction in RTT during wakefulness, there is still a significant lack of information regarding the same during sleep. Therefore, our aim was to investigate cardiovascular autonomic modulation during sleep in subjects with RTT compared to an age-matched healthy control group (HC). MethodA complete overnight polysomnographic (PSG) recording was obtained from 11 patients with Rett syndrome (all females, 10 ± 4 years old) and 11 HC (all females, 11 ± 4 years old; p = 0.48). Electrocardiogram and breathing data were extracted from PSG and divided into wake, non-REM, and REM sleep stages. Cardiac autonomic control was assessed using symbolic non-linear heart rate variability analysis. The symbolic analysis identified three patterns: 0 V% (sympathetic), 2UV%, and 2LV% (vagal). ResultsThe 0 V% was higher in the RTT group than in the HC group during wake, non-REM, and REM stages (p < 0.01), while the 2LV and 2UV% were lower during wake and sleep stages (p < 0.01). However, the 0 V% increased similarly from the wake to the REM stage in both RTT and HC groups. ConclusionsTherefore, the sympatho-vagal balance shifted towards sympathetic predominance and vagal withdrawal during wake and sleep in RTT, although cardiac autonomic dynamics were preserved during sleep.

Following your heart: Cardiac autonomic modulation as a feature of decision-making under ambiguity and risk

Decision-making requires a bidirectional flow of information from perception, emotion, and bodily behaviour. Heart rate variability (HRV) provides a non-invasive, cost-effective way to assess this connection. 112 healthy participants completed two established decision tasks under ambiguity and risk. Heart rate was continuously recorded at rest, during, and after task performance. To account for differences in cardiac modulation the sample was stratified by sex. Time, frequency, and non-linear HRV domains were selected to assess vagal modulation and sympatho-vagal balance. Vagally meditated HRV showed a pattern corresponding to a replenishment effect by increasing during decision-making in both tasks compared to rest, and then gradually returning to initial levels during recovery. This effect may indicate successful self-regulation, such as enhanced concentration, or emotional regulation. Regarding decision-making, women and men making disadvantageous decisions under ambiguity had higher vagally mediated HRV than those making advantageous decisions. Consistent with this finding are the results for decisions under risk for women. Contrary, men making disadvantageous decisions under risk, showed lower vagally mediated HRV than those making advantageous decisions. The results suggest that there are sex-specific differences to be investigated in the future. HRV analysis is an effective approach for differentiating somatic characteristics associated with decision-making performance.

Heart rate dynamics and asymmetry during sympathetic activity stimulation and post-stimulation recovery in ski mountaineers-a pilot exploratory study.

There is a lack of studies on non-linear heart rate (HR) variability in athletes. We aimed to assess the usefulness of short-term HR dynamics and asymmetry parameters to evaluate the neural modulation of cardiac activity based on non-stationary RR interval series by studying their changes during sympathetic nervous system activity stimulation (isometric handgrip test) and post-stimulation recovery in professional ski mountaineers. The correlation between the changes in the parameters and the respiratory rate (RespRate) and also the duration of the career was analyzed. Short-term (5 min) and ultra-short-term (1 min) rates of patterns with no variations (0V), number of acceleration runs of length 1 (AR1), and short-term Porta's Index were greater, whereas Guzik's Index (GI) was smaller during sympathetic stimulation compared to rest. GI increased and the number of AR1 decreased during recovery. Greater increases in GI and RMSSD were associated with greater decreases in RespRate during recovery. Greater increases in RespRate from rest to short-term sympathetic stimulation were associated with greater increases in 0V (Max-min method) and AR1 but also with greater decreases in decelerations of short-term variance and accelerations and decelerations of long-term variance. Greater increases in 0V (Max-min method) and number of AR1 during sympathetic stimulation were associated with a shorter career duration. Greater decreases in these parameters during recovery were associated with a longer career duration. Changes in measures of HR dynamics and asymmetry, calculated based on short-term non-stationary RRi time series induced by sympathetic stimulation and post-stimulation recovery, reflected sympathovagal shift and were associated with condition-related alterations in RespRate and career duration in athletes who practice ski mountaineering.

Heart Rate Variability as a Tool for Seizure Prediction: A Scoping Review

The most critical burden for People with Epilepsy (PwE) is represented by seizures, the unpredictability of which severely impacts quality of life. The design of real-time warning systems that can detect or even predict ictal events would enhance seizure management, leading to high benefits for PwE and their caregivers. In the past, various research works highlighted that seizure onset is anticipated by significant changes in autonomic cardiac control, which can be assessed through heart rate variability (HRV). This manuscript conducted a scoping review of the literature analyzing HRV-based methods for detecting or predicting ictal events. An initial search on the PubMed database returned 402 papers, 72 of which met the inclusion criteria and were included in the review. These results suggest that seizure detection is more accurate in neonatal and pediatric patients due to more significant autonomic modifications during the ictal transitions. In addition, conventional metrics are often incapable of capturing cardiac autonomic variations and should be replaced with more advanced methodologies, considering non-linear HRV features and machine learning tools for processing them. Finally, studies investigating wearable systems for heart monitoring denoted how HRV constitutes an efficient biomarker for seizure detection in patients presenting significant alterations in autonomic cardiac control during ictal events.

A Systematic Review of the Relationship between Psychological Stress Protocols and Non-linear Heart Rate Variability

A Systematic Review of the Relationship between Psychological Stress Protocols and Non-linear Heart Rate Variability

Nonlinear Heart Rate Variability Analysis for Sleep Stage Classification Using Integration of Ballistocardiogram and Apple Watch.

Wearable or non-contact, non-intrusive devices present a practical alternative to traditional polysomnography (PSG) for daily assessment of sleep quality. Physiological signals have been known to be nonlinear and nonstationary as the body adapts to states of rest or activity. By integrating more sophisticated nonlinear methodologies, the accuracy of sleep stage identification using such devices can be improved. This advancement enables individuals to monitor and adjust their sleep patterns more effectively without visiting sleep clinics. Six participants slept for three cycles of at least three hours each, wearing PSG as a reference, along with an Apple Watch, an actigraphy device, and a ballistocardiography (BCG) bed sensor. The physiological signals were processed with nonlinear methods and trained with a long short-term memory (LSTM) model to classify sleep stages. Nonlinear methods, such as return maps with advanced techniques to analyze the shape and asymmetry in physiological signals, were used to relate these signals to the autonomic nervous system (ANS). The changing dynamics of cardiac signals in restful or active states, regulated by the ANS, were associated with sleep stages and quality, which were measurable. Approximately 73% agreement was obtained by comparing the combination of the BCG and Apple Watch signals against a PSG reference system to classify rapid eye movement (REM) and non-REM sleep stages. Utilizing nonlinear methods to evaluate cardiac dynamics showed an improved sleep quality detection with the non-intrusive devices in this study. A system of non-intrusive devices can provide a comprehensive outlook on health by regularly measuring sleeping patterns and quality over time, offering a relatively accessible method for participants. Additionally, a non-intrusive system can be integrated into a user's or clinic's bedroom environment to measure and evaluate sleep quality without negatively impacting sleep. Devices placed around the bedroom could measure user vitals over longer periods with minimal interaction from the user, representing their natural sleeping trends for more accurate health and sleep disorder diagnosis.

The effectiveness of time domain and nonlinear heart rate variability metrics in ultra-short time series.

Ultra short-term (UST) heart rate variability (HRV) has been used to establish normative HRV values. This study aims to investigate whether HRV metrics can capture changes in HRV from external stimuli, and whether these metrics remain effective under various recording length. Participants completed varying stimulating activities including viewing images, arithmetic tasks, and memory recall of viewed images. SDNN, RMSSD, pNN50, SD2, SD1/SD2, and DFA were extracted from the data. Comparing arithmetic calculation and the first minute of memory recall, SDNN, pNN50, SD2, and SD1/SD2 had significant HRV differences; this suggests that these metrics can distinguish the inherently different stimuli participants were exposed to. However, comparing first minute of viewing with that of the second, SDNN, pNN50, and SD2, presented some significant HRV differences during two inherently similar stimuli. Comparing the first 60-120 s during viewing, SDNN, pNN50, and SD2 also presented significant differences. Our results suggest that SDNN, pNN50, and SD2 may not be robust in evaluating UST HRVs in replacement of the standard short-term HRV. It may be beneficial to analyze multiple HRV metrics, particularly SD1/SD2, to achieve a more holistic understanding of the underlying physiology.

Examining Physiological Changes during Counter-Strike: Global Offensive (CS:GO) Performance in Recreational Male Esports Players

While the training of professional sports athletes and the factors determining sports success are based on well-established scientific research, esports training and markers of esports performance are not yet fully recognized or explored. Knowledge of the psychophysiological responses of the athlete’s body to esports competition is the necessary foundation for rational training management. The aim of the present study was to evaluate physiological stress while playing Counter-Strike: Global Offensive (CS:GO). Selected cardiovascular, hormonal, and biochemical indices were monitored to assess differences in stress responses between winners and losers. Twenty-two male players participated in the study (age 22.0 ± 2.0 years, CS:GO training experience 7.0 ± 2.2 years, training load 24.6 ± 11.5 h per week). Each player played two games during the CS:GO competition. The CS:GO tournament induced an increase in heart rate (HR), systolic blood pressure, and blood cortisol levels (C), and a decrease in the nonlinear heart rate variability (HRV) index based on the fractal correlation properties, called alpha1, of detrended fluctuation analysis (DFA-alpha1). In contrast, no changes were observed in blood levels of testosterone (T) and lactate (BLa). It was found that changes in physiological indices in players while playing CS:GO did not differentiate between winners and losers. The changes in the physiological parameters recorded during play indicate that CS:GO tournaments induce significant physiological arousal and can be considered a stressor.

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

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