State Anxiety and Nonlinear Dynamics of Heart Rate Variability in Students

Machine Learning, Deep Learning, and Data Preprocessing Techniques for Detecting, Predicting, and Monitoring Stress and Stress-Related Mental Disorders: Scoping Review

BACKGROUND

Mental stress and its consequent mental health disorders (MDs) constitute a significant public health issue. With the advent of machine learning (ML), there is potential to harness computational techniques for better understanding and addressing mental stress and MDs. This comprehensive review seeks to elucidate the current ML methodologies used in this domain to pave the way for enhanced detection, prediction, and analysis of mental stress and its subsequent MDs.

OBJECTIVE

This review aims to investigate the scope of ML methodologies used in the detection, prediction, and analysis of mental stress and its consequent MDs.

METHODS

Using a rigorous scoping review process with PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, this investigation delves into the latest ML algorithms, preprocessing techniques, and data types used in the context of stress and stress-related MDs.

RESULTS

A total of 98 peer-reviewed publications were examined for this review. The findings highlight that support vector machine, neural network, and random forest models consistently exhibited superior accuracy and robustness among all ML algorithms examined. Physiological parameters such as heart rate measurements and skin response are prevalently used as stress predictors due to their rich explanatory information concerning stress and stress-related MDs, as well as the relative ease of data acquisition. The application of dimensionality reduction techniques, including mappings, feature selection, filtering, and noise reduction, is frequently observed as a crucial step preceding the training of ML algorithms.

CONCLUSIONS

The synthesis of this review identified significant research gaps and outlines future directions for the field. These encompass areas such as model interpretability, model personalization, the incorporation of naturalistic settings, and real-time processing capabilities for the detection and prediction of stress and stress-related MDs.

Anxiety in oncology outpatients is associated with perturbations in pathways identified in anxiety focused network pharmacology research

PURPOSE

Evaluate for perturbed signaling pathways associated with subgroups of patients with low versus high levels of state anxiety. These pathways were compared to the pathways identified across eight network pharmacology studies of the anxiolytic effect(s) of a variety of compounds.

METHODS

Adult outpatients had a diagnosis of breast, gastrointestinal, gynecological, or lung cancer; had received chemotherapy within the preceding four weeks; and were scheduled to receive at least two additional cycles of chemotherapy. Latent profile analysis was used to identify subgroups of patients with distinct anxiety profiles based on Spielberger State Anxiety Inventory scores that were obtained six times over two cycles of chemotherapy. Blood samples were processed using RNA sequencing (i.e., RNA-seq sample, n = 244) and microarray (i.e., microarray sample; n = 256) technologies. Pathway perturbations were assessed using pathway impact analysis. Fisher's combined probability method was used to combine test results using a false discovery rate of 0.01.

RESULTS

In the RNA-seq sample, 62.3% and 37.7% of the patients were in the low- and high-anxiety classes, respectively. In the microarray sample, 61.3% and 38.7% were in the low and high-anxiety classes, respectively. Forty-one perturbed signaling pathways were identified. Eight of these pathways were common to those identified in the network pharmacology studies.

CONCLUSIONS

Findings increase our knowledge of the molecular mechanisms that underlie anxiety in patients receiving chemotherapy. This study provides initial insights into how anxiety in patients with cancer may share common mechanisms with anxiety in patients with other clinical conditions.

Cardioautonomic lability assessed by heart rate variability changes in Royal Canadian Mounted Police cadets during the cadet training program

Objective

The current study examined variations in cardioautonomic lability during the Royal Canadian Mounted Police (RCMP) Cadet Training Program (CTP) between cadets starting their training who did or did not screen positive for one or more mental health disorders (i.e., posttraumatic stress disorder [PTSD], major depressive disorder [MDD], social anxiety disorder [SAD], generalized anxiety disorder [GAD], panic disorder [PD], alcohol use disorder [AUD]).

Methods

Electrocardiogram (ECG) signals integrated into Hexoskin garments were used to record ECG and heart rate Over the 26-week CTP. There were 31 heart rate variability (HRV) parameters calculated using Kubios Premium HRV analysis software. Mann-Whitney U-tests were used to perform groupwise comparisons of participant raw values and HRV during the CTP.

Results

A total of 157 cadets (79% male) were screened for any mental disorder using self-report surveys and then grouped by positive and negative screening. Analyses indicated a statistically significant (p < 0.05) decrease in low frequency (LF): High Frequency (HF) variability during CTP, but only for cadets who endorsed clinically significant anxiety symptoms on the GAD-7 at the start of their training. There were no other statistically significant groupwise differences.

Conclusion

The results indicate the participants have excellent cardiac health overall and suggest potentially important differences between groups, such that cadets who endorsed clinically significant anxiety symptoms on the GAD-7 showed less variability in the LF:HF ratio over the course of the CTP. The relatively lower variability suggests decreased parasympathetic tone in those without clinically significant anxiety symptoms. The results also have important implications for future investigations of cardioautonomic dysfunction and chronic hypothalamic pituitary adrenal (HPA) axis deviations in policing populations with anxiety disorders; specifically, cardioautonomic inflexibility related to cardiovascular morbidity and mortality. In any case, the current results provide an important baseline for future cardiac research with cadets and serving officers.

Entropy-Based Multifractal Testing of Heart Rate Variability during Cognitive-Autonomic Interplay

Entropy-based and fractal-based metrics derived from heart rate variability (HRV) have enriched the way cardiovascular dynamics can be described in terms of complexity. The most commonly used multifractal testing, a method using q moments to explore a range of fractal scaling in small-sized and large-sized fluctuations, is based on detrended fluctuation analysis, which examines the power-law relationship of standard deviation with the timescale in the measured signal. A more direct testing of a multifractal structure exists based on the Shannon entropy of bin (signal subparts) proportion. This work aims to reanalyze HRV during cognitive tasks to obtain new markers of HRV complexity provided by entropy-based multifractal spectra using the method proposed by Chhabra and Jensen in 1989. Inter-beat interval durations (RR) time series were obtained in 28 students comparatively in baseline (viewing a video) and during three cognitive tasks: Stroop color and word task, stop-signal, and go/no-go. The new HRV estimators were extracted from the f/α singularity spectrum of the RR magnitude increment series, established from q-weighted stable (log-log linear) power laws, namely: (i) the whole spectrum width (MF) calculated as αmax - αmin; the specific width representing large-sized fluctuations (MFlarge) calculated as α0 - αq+; and small-sized fluctuations (MFsmall) calculated as αq- - α0. As the main results, cardiovascular dynamics during Stroop had a specific MF signature while MFlarge was rather specific to go/no-go. The way these new HRV markers could represent different aspects of a complete picture of the cognitive-autonomic interplay is discussed, based on previously used entropy- and fractal-based markers, and the introduction of distribution entropy (DistEn), as a marker recently associated specifically with complexity in the cardiovascular control.

Cardiovascular response to anticipatory and reactionary postural perturbations in young adults

NEW FINDINGS

What is the central question of this study? It has been suggested that the cardiovascular responses to a postural perturbation are centrally mediated and reflex mediated. We wanted to know the extent to which the cardiovascular responses to external perturbations could be executed in a feedforward manner, in anticipation of the perturbation. What is the main finding and its importance? We found no anticipatory component driving heart rate and systolic blood pressure responses, suggesting that reflexive mechanisms dominate cardiovascular regulation after a postural perturbation in young adults.

ABSTRACT

Cardiovascular responses to postural perturbations have been reported, but whether the cardiovascular responses to external perturbations could be executed in anticipation of the perturbation is unknown. The purpose of this study was to determine the effect of anticipated and reactionary perturbations on heart rate (HR) and systolic blood pressure (SBP) responses in healthy young adults. A secondary aim was to determine whether perceived state anxiety scores were correlated with the change in HR response during postural perturbation. Twenty healthy young adults stood on a treadmill and experienced two perturbation conditions (anticipatory vs. reactionary), each with two intensity levels (Step vs. No Step). The HR and SBP were collected continuously. Two-way repeated-measures statistical non-parametric mapping tests were used to compare HR and SBP responses to the perturbations over time (from -3 to +8 s). The results indicated that HR was significantly elevated in the higher intensity perturbations [Step vs. No Step, at 0.56-1.32 s (P < 0.0001) and 1.92-3.44 s (P < 0.0001) post-perturbation], while there were no differences in HR between perturbation types (anticipatory vs. reactionary) or in SBP between perturbation types and intensity levels. The perceived state anxiety scores did not differ between perturbation types and intensity levels but were correlated with the change in HR post-perturbation (P = 0.013). We suggest that reflexive mechanisms dominate cardiovascular regulation after anticipatory and reactionary perturbations. The data highlight the cardiovascular mechanism(s) associated with perturbations that should be considered when assessing postural stability in populations with poor balance performance.

The effects of left prefrontal stimulation on selective attention and emotional reactivity for positive and negative information

Transcranial direct current stimulation targeting lateral prefrontal areas may attenuate attentional vigilance for negative content and reduce emotional reactivity. However, little research to date has examined how such stimulation may affect attention towards and emotional reactivity to positive emotional content. The aim of this study was to examine whether anodal tDCS targeting the left dorsolateral prefrontal cortex would affect attentional bias towards either or both negative and positive content, and similarly, how it would impact emotional reactivity to negative and positive emotional content among healthy individuals. Unselected participants (N = 101) were recruited (Mage = 22.57, SD = 5.60; 66.33% female) and allocated to either an active or sham tDCS condition. Attentional bias was measured using an eye-tracking task involving negative-neutral and positive-neutral image pairs, followed by an emotional reactivity assessment task involving negative and positive video content (self-report and heart rate variability). Results showed no evidence that tDCS influenced attentional patterns towards either positive or negative information, nor was there evidence that tDCS influenced self-reported anxious mood or physiological arousal. However, participants in the active tDCS condition reported higher positive mood in response to both the positive and negative videos compared to those in the sham condition and also higher arousal in response to positive content and lower arousal in response to negative content, with those in the sham tDCS condition showing the reverse pattern of effects. As such, tDCS effects on emotional reactivity to positive and negative content were restricted to self-report measures.

Heart Rate Variability for Evaluating Psychological Stress Changes in Healthy Adults: A Scoping Review

The utility of heart rate variability (HRV) for characterizing psychological stress is primarily impacted by methodological considerations such as study populations, experienced versus induced stress, and method of stress assessment. Here, we review studies on the associations between HRV and psychological stress, examining the nature of stress, ways stress was assessed, and HRV metrics used. The review was performed according to the PRISMA guidelines on select databases. Studies that examined the HRV-stress relationship via repeated measurements and validated psychometric instruments were included (n = 15). Participant numbers and ages ranged between 10 and 403 subjects and 18 and 60 years, respectively. Both experimental (n = 9) and real-life stress (n = 6) have been explored. While RMSSD was the most reported HRV metric (n = 10) significantly associated with stress, other metrics, including LF/HF (n = 7) and HF power (n = 6) were also reported. Various linear and nonlinear HRV metrics have been utilized, with nonlinear metrics used less often. The most frequently used psychometric instrument was the State-Trait Anxiety Inventory (n = 10), though various other instruments have been reported. In conclusion, HRV is a valid measure of the psychological stress response. Standard stress induction and assessment protocols combined with validated HRV measures in different domains will improve the validity of findings.

Heart Rate Complexity and Autonomic Modulation Are Associated with Psychological Response Inhibition in Healthy Subjects

BACKGROUND

the ability to suppress/regulate impulsive reactions has been identified as common factor underlying the performance in all executive function tasks. We analyzed the HRV signals (power of high (HF) and low (LF) frequency, Sample Entropy (SampEn), and Complexity Index (CI)) during the execution of cognitive tests to assess flexibility, inhibition abilities, and rule learning.

METHODS

we enrolled thirty-six healthy subjects, recording five minutes of resting state and two tasks of increasing complexity based on 220 visual stimuli with 12 × 12 cm red and white squares on a black background.

RESULTS

at baseline, CI was negatively correlated with age, and LF was negatively correlated with SampEn. In Task 1, the CI and LF/HF were negatively correlated with errors. In Task 2, the reaction time positively correlated with the CI and the LF/HF ratio errors. Using a binary logistic regression model, age, CI, and LF/HF ratio classified performance groups with a sensitivity and specificity of 73 and 71%, respectively.

CONCLUSIONS

this study performed an important initial exploration in defining the complex relationship between CI, sympathovagal balance, and age in regulating impulsive reactions during cognitive tests. Our approach could be applied in assessing cognitive decline, providing additional information on the brain-heart interaction.

Heart Rate Variability in Elite International ITF Junior Davis Cup Tennis Players

The aim of the present study was to investigate the evolution of the HRV during an international team tennis tournament in elite junior tennis players. A total of 11 tennis players, with a mean age of 15.36 (0.67) from six nationalities, participated in this cross-sectional study. Participants were measured one day before the event, before the first match, and before the second match of the ITF Junior Davis Cup event. Each of the registers lasted 5 min and the time domain, frequency domain and non-linear variables were extracted. The tournament took place in Valencia (Spain). Results showed that there was not a significant decrease in the heart rate variability (HRV) induced by precompetitive stress. However, significant differences (p-value < 0.05) were found between baseline and second match pre-competition HRV values in low frequency (LFNu) (p-value = 0.008) and high frequency (HFNu) power (p-value = 0.008), LF/HF ratio (p-value = 0.008) and Sample Entropy (SampEn) (p-value = 0.033) variables. Furthermore, cognitive anxiety (measured by CSAI-2r) (p-value = 0.017) and anxiety (measured by STAI-S) (p-value = 0.042) were higher before the first match than before the second match. Coaches and physical trainers could use HRV to control and manage the precompetitive anxiety of junior tennis players. The experience in international tournaments and the familiarization with the environment in the second match could explain these results.

Contribution of Cardiorespiratory Coupling to the Irregular Dynamics of the Human Cardiovascular System

Irregularity is an important aspect of the cardiovascular system dynamics. Numerical indices of irregularity, such as the largest Lyapunov exponent and the correlation dimension estimated from interbeat interval time series, are early markers of cardiovascular diseases. However, there is no consensus on the origin of irregularity in the cardiovascular system. A common hypothesis suggests the importance of nonlinear bidirectional coupling between the cardiovascular system and the respiratory system for irregularity. Experimental investigations of this theory are severely limited by the capabilities of modern medical equipment and the nonstationarity of real biological systems. Therefore, we studied this problem using a mathematical model of the coupled cardiovascular system and respiratory system. We estimated and compared the numerical indices of complexity for a model simulating the cardiovascular dynamics in healthy subjects and a model with blocked regulation of the respiratory frequency and amplitude, which disturbs the coupling between the studied systems.

Association between mental illness and blood pressure variability: a systematic review

Background

Mental illness represents a major global burden of disease worldwide. It has been hypothesised that individuals with mental illness have greater blood pressure fluctuations that lead to increased cardiovascular risk and target organ damage. This systematic review aims to (i) investigate the association between mental illness and blood pressure variability (BPV) and (ii) describe methods of BPV measurements and analysis which may affect pattern and degree of variability.

Methods

Four electronic databases were searched from inception until 2020. The quality assessment was performed using STROBE criteria. Studies were included if they investigated BPV (including either frequency or time domain analysis) in individuals with mental illness (particularly anxiety/generalised anxiety disorder, depression/major depressive disorder, panic disorder and hostility) and without hypertension. Two authors independently screened titles, abstracts and full texts. A third author resolved any disagreements.

Results

Twelve studies met the inclusion criteria. Three studies measured short-term BPV, two measured long-term BPV and seven measured ultra-short-term BPV. All studies related to short-term BPV using ambulatory and home blood pressure monitoring found a higher BPV in individuals with depression or panic disorder. The two studies measuring long-term BPV were limited to the older population and found mixed results. Mental illness is significantly associated with an increased BPV in younger and middle-aged adults. All studies of ultra-short-term BPV using standard cardiac autonomic assessment; non-invasive continuous finger blood pressure and heart rate signals found significant association between BPV and mental illness. A mixed result related to degree of tilt during tilt assessment and between controlled and spontaneous breathing were observed in patients with psychological state.

Conclusions

Current review found that people with mental illness is significantly associated with an increased BPV regardless of age. Since mental illness can contribute to the deterioration of autonomic function (HRV, BPV), early therapeutic intervention in mental illness may prevent diseases associated with autonomic dysregulation and reduce the likelihood of negative cardiac outcomes. Therefore, these findings may have important implications for patients' future physical health and well-being, highlighting the need for comprehensive cardiovascular risk reduction.

Human state anxiety classification framework using EEG signals in response to exposure therapy

Human anxiety is a grave mental health concern that needs to be addressed in the appropriate manner in order to develop a healthy society. In this study, an objective human anxiety assessment framework is developed by using physiological signals of electroencephalography (EEG) and recorded in response to exposure therapy. The EEG signals of twenty-three subjects from an existing database called "A Database for Anxious States which is based on a Psychological Stimulation (DASPS)" are used for anxiety quantification into two and four levels. The EEG signals are pre-processed using appropriate noise filtering techniques to remove unwanted ocular and muscular artifacts. Channel selection is performed to select the significantly different electrodes using statistical analysis techniques for binary and four-level classification of human anxiety, respectively. Features are extracted from the data of selected EEG channels in the frequency domain. Frequency band selection is applied to select the appropriate combination of EEG frequency bands, which in this study are theta and beta bands. Feature selection is applied to the features of the selected EEG frequency bands. Finally, the selected subset of features from the appropriate frequency bands of the statistically significant EEG channels were classified using multiple machine learning algorithms. An accuracy of 94.90% and 92.74% is attained for two and four-level anxiety classification using a random forest classifier with 9 and 10 features, respectively. The proposed state anxiety classification framework outperforms the existing anxiety detection framework in terms of accuracy with a smaller number of features which reduces the computational complexity of the algorithm.

A calming hug: Design and validation of a tactile aid to ease anxiety

Anxiety disorders affect approximately one third of people during their lifetimes and are the ninth leading cause of global disability. Current treatments focus on therapy and pharmacological interventions. However, therapy is costly and pharmacological interventions often have undesirable side-effects. Healthy people also regularly suffer periods of anxiety. Therefore, a non-pharmacological, intuitive, home intervention would be complementary to other treatments and beneficial for non-clinical groups. Existing at-home anxiety aids, such as guided meditations, typically employ visual and/or audio stimuli to guide the user into a calmer state. However, the tactile sense has the potential to be a more natural modality to target in an anxiety-calming device. The tactile domain is relatively under-explored, but we suggest that there are manifold physiological and affective qualities of touch that lend it to the task. In this study we demonstrate that haptic technology can offer an enjoyable, effective and widely accessible alternative for easing state anxiety. We describe a novel huggable haptic interface that pneumatically simulates slow breathing. We discuss the development of this interface through a focus group evaluating five prototypes with embedded behaviours (‘breathing’, ‘purring’, ‘heartbeat’ and ‘illumination’). Ratings indicated that the ‘breathing’ prototype was most pleasant to interact with and participants described this prototype as ‘calming’ and ‘soothing’, reminding them of a person breathing. This prototype was developed into an ergonomic huggable cushion containing a pneumatic chamber powered by an external pump allowing the cushion to ‘breathe’. A mixed-design experiment (n = 129) inducing anxiety through a group mathematics test found that the device was effective at reducing pre-test anxiety compared to a control (no intervention) condition and that this reduction in anxiety was indistinguishable from that of a guided meditation. Our findings highlight the efficacy of this interface, demonstrating that haptic technologies can be effective at easing anxiety. We suggest that the field should be explored in more depth to capture the nuances of different modalities in relation to specific situations and trait characteristics.

Degraded Psychophysiological Status in Caregivers and Human Resources Staff during a COVID-19 Peak Unveiled by Psychological and HRV Testing at Workplace

During COVID-19 pandemic peaks, healthcare professionals are a frontline workforce that deals with death on an almost daily basis and experiences a marked increase in workload. Returning home is also associated with fear of contaminating or be contaminated. An obvious consequence is stress accumulation and associated risks, especially in caregivers in mobility and possibly in human resource teams managing mobility. Here, during the second pandemic peak, we designed a 15-min testing procedure at the workplace, combining HADS and Brief COPE questionnaires with heart rate variability (HRV) recordings to evaluate psychophysiological status in four groups: caregivers in mobility (MOB); human resources teams managing mobility (ADM); caregivers without mobility (N-MOB); and university researchers teaching online (RES). Anxiety, depression, coping strategies, vagally-mediated heart rate regulation, and nonlinear dynamics (entropy) in cardiac autonomic control were quantified. Anxiety reached remarkably high levels in both MOB and ADM, which was reflected in vagal and nonlinear HRV markers. ADM maintained a better problem-solving capacity. MOB and N-MOB exhibited degraded problem-solving capacity. Multivariate approaches show how combining psychological and physiological markers helps draw highly group-specific psychophysiological profiles. Entropy in HRV and problem-solving capacity were highly relevant for that. Combining HADS and Brief COPE questionnaires with HRV testing at the workplace may provide highly relevant cues to manage mobility during crises as well as prevent health risks, absenteeism, and more generally malfunction incidents at hospitals.

Assessing rheoencephalography dynamics through analysis of the interactions among brain and cardiac networks during general anesthesia

Cerebral blood flow (CBF) reflects the rate of delivery of arterial blood to the brain. Since no nutrients, oxygen or water can be stored in the cranial cavity due to space and pressure restrictions, a continuous perfusion of the brain is critical for survival. Anesthetic procedures are known to affect cerebral hemodynamics, but CBF is only monitored in critical patients due, among others, to the lack of a continuous and affordable bedside monitor for this purpose. A potential solution through bioelectrical impedance technology, also known as rheoencephalography (REG), is proposed, that could fill the existing gap for a low-cost and effective CBF monitoring tool. The underlying hypothesis is that REG signals carry information on CBF that might be recovered by means of the application of advanced signal processing techniques, allowing to track CBF alterations during anesthetic procedures. The analysis of REG signals was based on geometric features extracted from the time domain in the first place, since this is the standard processing strategy for this type of physiological data. Geometric features were tested to distinguish between different anesthetic depths, and they proved to be capable of tracking cerebral hemodynamic changes during anesthesia. Furthermore, an approach based on Poincaré plot features was proposed, where the reconstructed attractors form REG signals showed significant differences between different anesthetic states. This was a key finding, providing an alternative to standard processing of REG signals and supporting the hypothesis that REG signals do carry CBF information. Furthermore, the analysis of cerebral hemodynamics during anesthetic procedures was performed by means of studying causal relationships between global hemodynamics, cerebral hemodynamics and electroencephalogram (EEG) based-parameters. Interactions were detected during anesthetic drug infusion and patient positioning (Trendelenburg positioning and passive leg raise), providing evidence of the causal coupling between hemodynamics and brain activity. The provided alternative of REG signal processing confirmed the hypothesis that REG signals carry information on CBF. The simplicity of the technology, together with its low cost and easily interpretable outcomes, should provide a new opportunity for REG to reach standard clinical practice. Moreover, causal relationships among the hemodynamic physiological signals and brain activity were assessed, suggesting that the inclusion of REG information in depth of anesthesia monitors could be of valuable use to prevent unwanted CBF alterations during anesthetic procedures.

The Ava bracelet for collection of fertility and pregnancy data in free-living conditions: An exploratory validity and acceptability study

Objective

To evaluate the validity and acceptability of the Ava bracelet for collecting heart rate, sleep, mood, and physical activity data among reproductive-aged women (pregnant and nonpregnant) under free-living conditions.

Methods

Thirty-three participants wore the Ava bracelet on their non-dominant wrist and reported mood and physical activity in the Ava mobile application for seven nights. Criterion validity was determined by comparing the Ava bracelet heart rate and sleep duration measures to criterion measures from the Polar chest strap and ActiGraph GTX3 + accelerometer. Construct validity was determined by comparing self-report measures and the heart rate variability ratio collected in the Ava mobile application to previously validated measures. Acceptability was evaluated using the modified Acceptability of Health Apps among Adolescents Scale.

Results

Mean absolute percentage error was 11.4% for heart rate and 8.5% for sleep duration. There was no meaningful difference between the Ava bracelet, ActiGraph, and construct a measure of sleep quality. Compared to construct measures, Ava bracelet heart rate variability had a significant low negative correlation (r:−0.28), mood had a significant low positive correlation (r : 0.39), and physical activity level had a significant low (r_{level of physical activity}: 0.56) to moderate positive correlation (r_{MET−minutes/week}: 0.71). The acceptability of the Ava bracelet was high for fertility and low for pregnancy tracking.

Conclusion

Preliminary evidence suggests the Ava bracelet and mobile application estimates of sleep and heart rate are not equivalent to criterion measures in free-living conditions. Further research is needed to establish its utility for collecting prospective, subjective data throughout periods of preconception and pregnancy.

Heart Rate Modeling and Prediction Using Autoregressive Models and Deep Learning

Physiological time series are affected by many factors, making them highly nonlinear and nonstationary. As a consequence, heart rate time series are often considered difficult to predict and handle. However, heart rate behavior can indicate underlying cardiovascular and respiratory diseases as well as mood disorders. Given the importance of accurate modeling and reliable predictions of heart rate fluctuations for the prevention and control of certain diseases, it is paramount to identify models with the best performance in such tasks. The objectives of this study were to compare the results of three different forecasting models (Autoregressive Model, Long Short-Term Memory Network, and Convolutional Long Short-Term Memory Network) trained and tested on heart rate beats per minute data obtained from twelve heterogeneous participants and to identify the architecture with the best performance in terms of modeling and forecasting heart rate behavior. Heart rate beats per minute data were collected using a wearable device over a period of 10 days from twelve different participants who were heterogeneous in age, sex, medical history, and lifestyle behaviors. The goodness of the results produced by the models was measured using both the mean absolute error and the root mean square error as error metrics. Despite the three models showing similar performance, the Autoregressive Model gave the best results in all settings examined. For example, considering one of the participants, the Autoregressive Model gave a mean absolute error of 2.069 (compared to 2.173 of the Long Short-Term Memory Network and 2.138 of the Convolutional Long Short-Term Memory Network), achieving an improvement of 5.027% and 3.335%, respectively. Similar results can be observed for the other participants. The findings of the study suggest that regardless of an individual's age, sex, and lifestyle behaviors, their heart rate largely depends on the pattern observed in the previous few minutes, suggesting that heart rate can be reasonably regarded as an autoregressive process. The findings also suggest that minute-by-minute heart rate prediction can be accurately performed using a linear model, at least in individuals without pathologies that cause heartbeat irregularities. The findings also suggest many possible applications for the Autoregressive Model, in principle in any context where minute-by-minute heart rate prediction is required (arrhythmia detection and analysis of the response to training, among others).

Telemetric data collection should be standard in modern experimental cardiovascular research

Cardiovascular (CV) health is often expressed by changes in heart rate and blood pressure, the physiological record of which may be affected by moving, anaesthesia, handling, time of day and many other factors in rodents. Telemetry measurement minimises these modulations and enables more accurate physiological recording of heart rate and blood pressure than non-invasive methods. Measurement of arterial blood pressure by telemetry requires implanting a catheter tip into the artery. Telemetry enables us to sample physiological parameters with a high frequency continuously for several months. By measuring the pressure in the artery using telemetry, we can visualize pressure changes over a heart cycle as the pressure wave. From the pressure wave, we can subtract systolic, diastolic, mean and pulse pressure. From the beat-to-beat interval (pressure wave) and the RR' interval (electrocardiogram), we can derive the heart rate. From beat-to-beat variability, we can evaluate the autonomic nervous system's activity and spontaneous baroreflex sensitivity and their impact on CV activity. On a long-term scale, circadian variability of CV parameters is evident. Circadian variability is the result of the circadian system's activity, which synchronises and organises many activities in the body, such as autonomic and reflex modulation of the CV system and its response to load over the day. In the presented review, we aimed to discuss telemetry devices, their types, implantation, set-up, limitations, short-term and long-term variability of heart rate and blood pressure in CV research. Data collection by telemetry should be, despite some limitations, standard in modern experimental CV research.

Overlap between irritable bowel syndrome and hypermobile Ehlers-Danlos syndrome: An unexplored clinical phenotype?

Irritable bowel syndrome (IBS) is common, but its cause remains unknown. IBS patients present with gastrointestinal (GI) symptoms such as abdominal pain with altered bowel habits; however, some patients also have non-GI symptoms including muscle and joint pains. It is thus plausible that within large IBS cohorts, subgroups exist with distinct clinical phenotypes. Yet, these subgroups have not been clearly identified or characterized. Due to lack of segmentation, treatment-focused symptomatic management is similar for all with IBS and follows indiscriminate algorithms regardless of possible differing clinical phenotype. This universal approach to IBS management may account for the reported lack of efficacy of treatment. One emerging subgroup receiving increasing attention is that with overlap IBS and the underlying heritable connective tissue disorder, hypermobile Ehlers-Danlos syndrome (hEDS). Current evidence suggests that up to 62% of patients with hEDS suffer from IBS. However, despite recognition of the presence of IBS in hEDS, this overlap IBS/hEDS group has not been characterized and these patients are managed in a similar way to those with IBS alone. Future studies are required to characterize and deep phenotype in this overlap IBS/hEDS group.

Heart Rate Variability in Psychology: A Review of HRV Indices and an Analysis Tutorial

The use of heart rate variability (HRV) in research has been greatly popularized over the past decades due to the ease and affordability of HRV collection, coupled with its clinical relevance and significant relationships with psychophysiological constructs and psychopathological disorders. Despite the wide use of electrocardiograms (ECG) in research and advancements in sensor technology, the analytical approach and steps applied to obtain HRV measures can be seen as complex. Thus, this poses a challenge to users who may not have the adequate background knowledge to obtain the HRV indices reliably. To maximize the impact of HRV-related research and its reproducibility, parallel advances in users' understanding of the indices and the standardization of analysis pipelines in its utility will be crucial. This paper addresses this gap and aims to provide an overview of the most up-to-date and commonly used HRV indices, as well as common research areas in which these indices have proven to be very useful, particularly in psychology. In addition, we also provide a step-by-step guide on how to perform HRV analysis using an integrative neurophysiological toolkit, NeuroKit2.

Entropy and Multifractal-Multiscale Indices of Heart Rate Time Series to Evaluate Intricate Cognitive-Autonomic Interactions

Recent research has clarified the existence of a networked system involving a cortical and subcortical circuitry regulating both cognition and cardiac autonomic control, which is dynamically organized as a function of cognitive demand. The main interactions span multiple temporal and spatial scales and are extensively governed by nonlinear processes. Hence, entropy and (multi)fractality in heart period time series are suitable to capture emergent behavior of the cognitive-autonomic network coordination. This study investigated how entropy and multifractal-multiscale analyses could depict specific cognitive-autonomic architectures reflected in the heart rate dynamics when students performed selective inhibition tasks. The participants (N=37) completed cognitive interference (Stroop color and word task), action cancellation (stop-signal) and action restraint (go/no-go) tasks, compared to watching a neutral movie as baseline. Entropy and fractal markers (respectively, the refined composite multiscale entropy and multifractal-multiscale detrended fluctuation analysis) outperformed other time-domain and frequency-domain markers of the heart rate variability in distinguishing cognitive tasks. Crucially, the entropy increased selectively during cognitive interference and the multifractality increased during action cancellation. An interpretative hypothesis is that cognitive interference elicited a greater richness in interactive processes that form the central autonomic network while action cancellation, which is achieved via biasing a sensorimotor network, could lead to a scale-specific heightening of multifractal behavior.

Life events are associated with elevated heart rate and reduced heart complexity to acute psychological stress

The current study examined whether the exposure to life events and reported impact of life events are associated with altered cardiac reactivity to an acute psychological stressor. Participants (N = 69) completed the Life Experience Survey (LES) and Positive and Negative Affect Schedule (PANAS) and undertook a standardized social-evaluative stress task. Cardiac activity was measured via heart rate and non-linear heart rate variability (HRV) indices Sample Entropy, SD1, SD2 and SD1/SD2 ratio. Heart rate and non-linear HRV were measured before, during and after stress exposure. Findings suggest higher heart rate reactivity in individuals reporting higher number and impact of negative and total life events. Decreases in Sample Entropy were evident for number as well as impact of life events. No associations were found for SD1, SD2 and SD1/SD2 ratio. Findings suggest that life-events are associated with elevated heart rate and diminished heart rate complexity in response to acute stress.

Physiological Resonance in Empathic Stress: Insights from Nonlinear Dynamics of Heart Rate Variability

Because most humans live and work in populated environments, researchers recently took into account that people may not only experience first-hand stress, but also second-hand stress related to the ability to empathically share another person’s stress response. Recently, researchers have begun to more closely examine the existence of such empathic stress and highlighted the human propensity to physiologically resonate with the stress responses of others. As in case of first-hand stress, empathic stress could be deleterious for health if people experience exacerbated activation of hypothalamic–pituitary–adrenal and autonomic nervous systems. Thus, exploring empathic stress in an observer watching someone else experiencing stress is critical to gain a better understanding of physiological resonance and conduct strategies for health prevention. In the current study, we investigated the influence of empathic stress responses on heart rate variability (HRV) with a specific focus on nonlinear dynamics. Classic and nonlinear markers of HRV time series were computed in both targets and observers during a modified Trier social stress test (TSST). We capitalized on multiscale entropy, a reliable marker of complexity for depicting neurovisceral interactions (brain-to-heart and heart-to-brain) and their role in physiological resonance. State anxiety and affect were evaluated as well. While classic markers of HRV were not impacted by empathic stress, we showed that the complexity marker reflected the existence of empathic stress in observers. More specifically, a linear model highlighted a physiological resonance phenomenon. We conclude on the relevance of entropy in HRV dynamics, as a marker of complexity in neurovisceral interactions reflecting physiological resonance in empathic stress.

State anxiety and cardiovascular activity in an academic examination

Exam is an academic stressor that frequently triggers the affective reaction of anxiety, as well as psychophysiological changes in the autonomic nervous system. Anxiety is a negative affective variable associated with a low level of performance. This study examined the impact of an academic exam on state anxiety (SA) levels and the effects on cardiovascular activity during its performance, as well as its possible influence on the score. The study group was composed of 122 female university students. Cardiovascular responses (heart rate [HR], diastolic blood pressure, and systolic blood pressure) were recorded continuously in three phases (before, during, and after the exam) for each participant. The SA was obtained with the State-Trait Anxiety Inventory (STAI) before the exam. Then, those with extremely low and high SA scores were assigned to the low and high anxiety groups, respectively. The exam score reflected the performance level. The results partially confirmed our hypotheses. The high SA group showed significant fluctuations in cardiovascular activity; in particular, the HRs were higher than in the low SA group during the exam (not in diastolic and systolic pressures, respectively). On the other hand, the high SA group showed lower performance expectations scores than the low SA group, and the level of performance was similar in the two groups. Therefore, the exam confirmed changes in the HR with respect to the SA level, with no significant impact on performance.

Physiological responses during paramedics' simulated driving tasks

BACKGROUND

Most ambulance collisions happen in emergency driving conditions and are caused by human factors.

OBJECTIVE

This study investigated the influence of human factors associated with time pressure, patient-care intervention, and health status on the physiological responses of simulated emergency driving tasks.

METHODS

A cohort of seventeen experienced paramedics performed a battery of three simulated diving tasks. The driving tasks were a non-urgent and two urgent driving simulations (one to the scene and one to the hospital). The second urgent driving task was preceded by a patient-care simulation (unstable cardiac patient with cardiopulmonary resuscitation).

RESULTS

The physiological responses between the three driving tasks were not significantly different due to time pressure and patient-care intervention. It is postulated that the physiological response of experienced paramedics was influenced by the fact that they are accustomed to handling stressful situations daily. Furthermore, it was observed that paramedics with health conditions were more physiologically aroused during the urgent driving scenarios (pre and post-intervention), suggesting they might have an elevated risk of collision when they drive with urgency. Paramedics with health conditions also had higher physiological responses for the post-intervention baseline, leading to a longer recovery time period, which might represent an elevated risk of developing chronic health problems or amplifying existing ones.

CONCLUSIONS

The findings of this research suggest that experienced paramedics manage the influence of time pressure and the impact of challenging patient-care well. Paramedics with health conditions represent an elevated risk of collision.

Higher levels of Depressive Symptoms are Associated with Increased Resting-State Heart Rate Variability and Blunted Reactivity to a Laboratory Stress Task among Healthy Adults

Laboratory stress tasks induce strong changes in linear and non-linear indices of heart rate variability (HRV) among healthy adults, due to a task-induced parasympathetic withdrawal. Previous findings suggested that negative affectivity and its correlates (i.e., depressive symptoms, anxiety, hostility, type D personality, and situational stress) could profoundly affect autonomic activity. However, to date no studies considered these psychological dimensions simultaneously while trying to disentangle their acute effects on HRV during a laboratory stress task. A total of 65 healthy participants completed a battery of questionnaires and later underwent a psychosocial stress protocol, which involves a stressful and a non-stressful mental arithmetic task, with the latter serving as a control condition for the former. During the entire procedure, autonomic activity was recorded through a portable ECG device. We analysed longitudinal changes in HRV indices using Mixed Models, taking into account respiration rates and the associations between psychophysiological variables through bivariate Pearson's r (partial) correlation indices. We found significant changes in linear (e.g., HF power, RMSSD) and non-linear (e.g., Poincaré Plot and Correlation Dimension D2) HRV indices during the procedure, with the lowest point reached during the stressful mental arithmetic task. Interestingly, only depressive symptomatology was significantly and positively related to a higher resting-state HRV and to a blunted reactivity to the stress task, even after controlling for baseline values. Results suggest that healthy individuals with higher levels of depressive symptoms could experience atypical cardiovascular responses to stressful events: several speculative interpretations, considering autonomic, behavioral, and motivational dysregulations, are discussed.

Evaluation of a brief interval exercise training (IET) intervention for first-time prisoners with elevated anxiety symptoms

ABSTRACT Background: Exercise training has a history of alleviating anxiety in various populations, but research into its effects on prison inmates is limited. Confinement to prison is a highly distressing event for those who have never experienced incarceration, which can dramatically increase anxiety-related symptoms and may exacerbate suicidal risk. Methods: Thirty-seven first-time prisoners with elevated anxiety symptoms completed the State-Trait Anxiety Inventory before and after a 6-week long treatment period consisting of interval exercise training (IET; n = 20) or no intervention (waiting-list; n = 17). Prisoners in the IET intervention had to exercise three times per week (40 min per session) under the supervision of the first and/or second author. Exercise intensity was self-monitored using the Borg's RPE-15 scale, with targets in the range 13-15 ("somewhat hard"-"hard"). Results: Those who received the IET intervention showed a significantly greater reduction in anxiety than prisoners in the waiting-list. The effect size for IET was of moderate-to-large magnitude (Cohen's d = -0.71). Conclusion: The authors conclude that the lower levels of anxiety reported following IET suggest that supervised exercise training is an effective coping strategy to deal with incarceration. Trial registration: ClinicalTrials.gov identifier: NCT04019171.

Entropy in Heart Rate Dynamics Reflects How HRV-Biofeedback Training Improves Neurovisceral Complexity during Stress-Cognition Interactions

Despite considerable appeal, the growing appreciation of biosignals complexity reflects that system complexity needs additional support. A dynamically coordinated network of neurovisceral integration has been described that links prefrontal-subcortical inhibitory circuits to vagally-mediated heart rate variability. Chronic stress is known to alter network interactions by impairing amygdala functional connectivity. HRV-biofeedback training can counteract stress defects. We hypothesized the great value of an entropy-based approach of beat-to-beat biosignals to illustrate how HRVB training restores neurovisceral complexity, which should be reflected in signal complexity. In thirteen moderately-stressed participants, we obtained vagal tone markers and psychological indexes (state anxiety, cognitive workload, and Perceived Stress Scale) before and after five-weeks of daily HRVB training, at rest and during stressful cognitive tasking. Refined Composite Multiscale Entropy (RCMSE) was computed over short time scales as a marker of signal complexity. Heightened vagal tone at rest and during stressful tasking illustrates training benefits in the brain-to-heart circuitry. The entropy index reached the highest significance levels in both variance and ROC curves analyses. Restored vagal activity at rest correlated with gain in entropy. We conclude that HRVB training is efficient in restoring healthy neurovisceral complexity and stress defense, which is reflected in HRV signal complexity. The very mechanisms that are involved in system complexity remain to be elucidated, despite abundant literature existing on the role played by amygdala in brain interconnections.

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.

Diagnostics of coupling between low-frequency loops in cardiovascular autonomic control in adults, newborns and mathematical model using cross-recurrence analysis

The aim of study is to investigate effectiveness of cross-recurrence analysis for the detection of coupling between the loops of heart rate and vessel tone sympathetic control. The cross-recurrence analysis is applied to the interbeat intervals and photopletysmographic signals from the mathematical model of cardiovascular system and from adults and newborn children. The model is examined under the conditions of the four experiments: with fully operational autonomic control, autonomic control weakened by 40%, autonomic control weakened by 70% and autonomic blockade. The coupling is most pronounced in adult subjects and the model with fully operational autonomic control, while it is absent under the autonomic blockade. Autonomic control is also not fully developed in newborn children. As the result, smaller coupling strength is expected. The results of cross-recurrence analysis of the model and experimental data are compared with the results of coupling detection based on the analysos of phase synchronization. Synchronization index demonstrates good correlation with the coupling strength in the model and weak coupling in newborn children in relation to adult subjects. In both cases, no correlation is observed between the synchronization index and the results of cross-recurrence analysis.

Alterations in heart-brain interactions under mild stress during a cognitive task are reflected in entropy of heart rate dynamics

Many people experience mild stress in modern society which raises the need for an improved understanding of psychophysiological responses to stressors. Heart rate variability (HRV) may be associated with a flexible network of intricate neural structures which are dynamically organized to cope with diverse challenges. HRV was obtained in thirty-three healthy participants performing a cognitive task both with and without added stressors. Markers of neural autonomic control and neurovisceral complexity (entropy) were computed from HRV time series. Based on individual anxiety responses to the experimental stressors, two subgroups were identified: anxiety responders and non-responders. While both vagal and entropy markers rose during the cognitive task alone in both subgroups, only entropy decreased when stressors were added and exclusively in anxiety responders. We conclude that entropy may be a promising marker of cognitive tasks and acute mild stress. It brings out a new central question: why is entropy the only marker affected by mild stress? Based on the neurovisceral integration model, we hypothesized that neurophysiological complexity may be altered by mild stress, which is reflected in entropy of the cardiac output signal. The putative role of the amygdala during mild stress, in modulating the complexity of a coordinated neural network linking brain to heart, is discussed.

Autonomic control is a source of dynamical chaos in the cardiovascular system

The origin of complex irregular dynamics in a cardiovascular system is still being actively debated. Some hypotheses suggest the crucial role of stochastic modulation of cardiovascular parameters, while others argue for the importance of cardiac pacemakers' chaotic deterministic dynamics. In the present study, we estimate the largest Lyapunov exponent and the correlation dimension for the 4-h experimental interbeat intervals and the chaotic signals generated by the mathematical model of the cardiovascular system. We study the complexity of the mathematical model for such cases as the autonomic blockade, the exclusion of all the stochastic components, and the absence of variability of respiration. The obtained results suggest that the complexity of the heart rate variability is largely due to the chaotic dynamics in the loops of autonomic control of circulation.

Parasympathetic activity correlates with subjective and brain responses to rectal distension in healthy subjects but not in non-constipated patients with irritable bowel syndrome

The nociceptive and autonomic nervous systems (ANS) are significantly intertwined. Decoupling of these systems may occur in pathological pain conditions, including irritable bowel syndrome (IBS). We investigated ANS activity and its association with visceral perception and brain activity during rectal distention in 27 patients with non-constipated IBS and 33 controls by assessing heart rate variability (HRV) using electrocardiography at rest, before, and during colorectal distention. Brain responses to colorectal distention were measured using functional magnetic resonance imaging and correlated with individual ANS function parameters. The IBS group displayed blunted sympathovagal balance [low/high-frequency ratio (LF:HF) of HRV] in response to colorectal distention compared with controls (P = 0.003). In controls, basal parasympathetic tone (HF component of HRV) was significantly negatively correlated with toleration threshold to the rectal distention, but not in patients with IBS (group comparison P = 0.04). Further, a positive correlation between baseline HF values and neural responses to rectal distension was found in the right caudate, bilateral dorsolateral anterior cingulate cortex, and pregenual anterior cingulate cortex in the control group but not in the IBS group. The results indicate abnormal interactions between ANS activity and the brain mechanisms underlying visceral perception in patients with IBS.

A Comparison of Stress Perception in International and Local First Semester Medical Students Using Psychometric, Psychophysiological, and Humoral Methods

(1) Medical doctors and medical students show increased psychological stress levels. International medical students seem to be particularly vulnerable. (2) We compared different methods of assessing stress levels in international and local first year medical students. First, study participants completed questionnaires related to stress, depression, empathy, and self-efficacy (MBI, PSQ, PHQ-9, JSPE-S, and GSE) at three separate points in time (T1 to T3). Second, their heart rate variabilities (HRVs) were recorded in an oral examination, a seminar, and in a relaxing situation. Third, hair samples were collected at the beginning and at the end of the semester to assess the cortisol concentration. (3) Included were 20 international and 20 local first semester medical students. At T1, we found considerable differences between international and local students in the JSPE-S; at T2 in the MBI factor "professional efficacy", the PHQ-9, and in the JSPE-S; and at T3 in the MBI factors "cynicism" and "professional efficacy", the PHQ-9, and in the JSPE-S. International and local students also differed concerning their HRVs during relaxation. Over the course of the semester, international students showed changes in the MBI factors "emotional exhaustion" and "professional efficacy", the PHQ-9, and the GSE. Local students showed changes in the GSE. No effects were found for students' hair cortisol concentrations. (4) All participants showed low levels of stress. However, while international students experienced their stress levels to decrease over the course of the semester, local students found their stress levels to increase.

Poincaré plot analysis of cerebral blood flow signals: Feature extraction and classification methods for apnea detection

OBJECTIVE

Rheoencephalography is a simple and inexpensive technique for cerebral blood flow assessment, however, it is not used in clinical practice since its correlation to clinical conditions has not yet been extensively proved. The present study investigates the ability of Poincaré Plot descriptors from rheoencephalography signals to detect apneas in volunteers.

METHODS

A group of 16 subjects participated in the study. Rheoencephalography data from baseline and apnea periods were recorded and Poincaré Plot descriptors were extracted from the reconstructed attractors with different time lags (τ). Among the set of extracted features, those presenting significant differences between baseline and apnea recordings were used as inputs to four different classifiers to optimize the apnea detection.

RESULTS

Three features showed significant differences between apnea and baseline signals: the Poincaré Plot ratio (SDratio), its correlation (R) and the Complex Correlation Measure (CCM). Those differences were optimized for time lags smaller than those recommended in previous works for other biomedical signals, all of them being lower than the threshold established by the position of the inflection point in the CCM curves. The classifier showing the best performance was the classification tree, with 81% accuracy and an area under the curve of the receiver operating characteristic of 0.927. This performance was obtained using a single input parameter, either SDratio or R.

CONCLUSIONS

Poincaré Plot features extracted from the attractors of rheoencephalographic signals were able to track cerebral blood flow changes provoked by breath holding. Even though further validation with independent datasets is needed, those results suggest that nonlinear analysis of rheoencephalography might be a useful approach to assess the correlation of cerebral impedance with clinical changes.

Linear and non-linear heart rate metrics for the assessment of anaesthetists' workload during general anaesthesia

BACKGROUND

Excessive workload may impact the anaesthetists' ability to adequately process information during clinical practice in the operation room and may result in inaccurate situational awareness and performance. This exploratory study investigated heart rate (HR), linear and non-linear heart rate variability (HRV) metrics and subjective ratings scales for the assessment of workload associated with the anaesthesia stages induction, maintenance and emergence.

METHODS

HR and HRV metrics were calculated based on five min segments from each of the three anaesthesia stages. The area under the receiver operating characteristics curve (AUC) of the investigated metrics was calculated to assess their ability to discriminate between the stages of anaesthesia. Additionally, a multiparametric approach based on logistic regression models was performed to further evaluate whether linear or non-linear heart rate metrics are suitable for the assessment of workload.

RESULTS

Mean HR and several linear and non-linear HRV metrics including subjective workload ratings differed significantly between stages of anaesthesia. Permutation Entropy (PeEn, AUC=0.828) and mean HR (AUC=0.826) discriminated best between the anaesthesia stages induction and maintenance. In the multiparametric approach using logistic regression models, the model based on non-linear heart rate metrics provided a higher AUC compared with the models based on linear metrics.

CONCLUSIONS

In this exploratory study based on short ECG segment analysis, PeEn and HR seem to be promising to separate workload levels between different stages of anaesthesia. The multiparametric analysis of the regression models favours non-linear heart rate metrics over linear metrics.

Effects of heart rate variability biofeedback training in athletes exposed to stress of university examinations

Introduction

Heart rate variability biofeedback (HRV-BFB) training, a method whereby one controls an unusually low breathing rate to reach cardiac coherence, has been shown to reduce anxiety and improve cardiac autonomic markers in diseased people, but much less is known about HRV-BFB benefits in healthy people. Here we investigated potential benefits in young competitors experiencing stress during university examinations as well as persistence of benefits after HRV-BFB training cessation.

Methods

A group of sports students (n = 12) practiced 5-min HRV-BFB training twice a day for 5-weeks using URGOfeel^® (URGOTECH) and was compared to a control group (n = 6). University examinations occurred immediately after HRV-BFB training (Exam1), then 12-weeks later (Exam2). Anxiety markers and cardiac autonomic markers were assessed at baseline, Exam1 and Exam2. Principal Component Analyses (PCA) that combined all these markers were computed at Exam1 and Exam2 to emphasize covariations.

Results

At Exam 1, immediately after HRV-BFB training cessation, the experimental group demonstrated greater autonomic markers but similar states of anxiety when compared to the Control group. Twelve weeks later at Exam2, autonomic markers were greater and anxiety scores were lesser among the experimental group. PCA highlighted covariations only within cardiac autonomic markers at Exam1. Rather, variations in cardiac markers were associated with anxiety markers at Exam2.

Conclusion

Short sessions of HRV-BFB training for a brief period of 5 weeks bring substantial benefits to autonomic markers and anxiety levels in young competitors. Here beneficial effects persisted for 12 weeks. Dissociated profiles of anxiety and cardiac autonomic adaptations shed new light on the role of the amygdala in heart-brain interactions after cardiac coherence training.

The validity of linear and non-linear heart rate metrics as workload indicators of emergency physicians

Background

It has been shown that linear and non-linear heart rate variability (HRV) metrics are suitable to assess workload of anesthetists administering anesthesia. In pre-hospital emergency care, these parameters have not yet been evaluated. We hypothesized that heart rate (HR) and HRV metrics discriminate between differing workload levels of an emergency physician.

Methods

Electrocardiograms were obtained from 13 emergency physicians. Mean HR, ten linear and seven non-linear HRV metrics were analyzed. For each sortie, four different levels of workload were defined. Mixed-effects models and the area under the receiver operating characteristics curve (AUC) were used to test and quantify the HR and HRV metrics’ ability to discriminate between levels of workload. This was conducted for mean HR and each HRV metric as well as for groups of metrics (time domain vs. frequency domain vs. non-linear metrics).

Results

The non-linear HRV metric Permutation entropy (PeEn) discriminated best between the time before the alarm and primary patient care (AUC = 0.998, 1st rank of 18 HRV metrics). In contrast, AUC of the mean HR was low (0.558, 17th rank). In the multivariable approach, the non-linear HRV metrics provided a higher AUC (0.998) compared to the frequency domain (0.677) and to the time domain metrics (0.680).

Conclusion

Non-linear heart rate metrics and, specifically, PeEn provided good validity for the assessment of different levels of a physician’s workload in the setting of pre-hospital emergency care. In contradiction to earlier findings, the physicians’ mean HR was not a valid marker of workload.

Heart rate variability metrics for fine-grained stress level assessment

BACKGROUND AND OBJECTIVES

In spite of the existence of a multitude of techniques that allow the estimation of stress from physiological indexes, its fine-grained assessment is still a challenge for biomedical engineering. The short-term assessment of stress condition overcomes the limits to stress characterization with long blocks of time and allows to evaluate the behaviour change in real-world settings and also the stress level dynamics. The aim of the present study was to evaluate time and frequency domain and nonlinear heart rate variability (HRV) metrics for stress level assessment using a short-time window.

METHODS

The electrocardiogram (ECG) signal from 14 volunteers was monitored using the Vital Jacket^TM while they performed the Trier Social Stress Test (TSST) which is a standardized stress-inducing protocol. Window lengths from 220 s to 50 s for HRV analysis were tested in order to evaluate which metrics could be used to monitor stress levels in an almost continuous way.

RESULTS

A sub-set of HRV metrics (AVNN, rMSSD, SDNN and pNN20) showed consistent differences between stress and non-stress phases, and showed to be reliable parameters for the assessment of stress levels in short-term analysis.

CONCLUSIONS

The AVNN metric, using 50 s of window length analysis, showed that it is the most reliable metric to recognize stress level across the four phases of TSST and allows a fine-grained analysis of stress effect as an index of psychological stress and provides an insight into the reaction of the autonomic nervous system to stress.