An efficient algorithm for spectral analysis of heart rate variability

Kinematic signature of high risk labored breathing revealed by novel signal analysis

Breathing patterns (respiratory kinematics) contain vital prognostic information. This dimension of physiology is not captured by conventional vital signs. We sought to determine the feasibility and utility of quantifying respiratory kinematics. Using inertial sensors, we analyzed upper rib, lower rib, and abdominal motion of 108 patients with respiratory symptoms during a hospital encounter (582 two-minute recordings). We extracted 34 features based on an explainable correspondence with well-established breathing patterns. K-means clustering revealed that respiratory kinematics had three dimensions apart from the respiratory rate. We represented these dimensions using respiratory rate variability, respiratory alternans (rib-predominant breaths alternating with abdomen-predominant ones), and recruitment of accessory muscles (increased upper rib excursion). Latent profile analysis of the kinematic measures revealed two profiles consistent with the established clinical constructs of labored and unlabored breathing. In logistic regression, the labored breathing profile improved model discrimination for critical illness beyond the Sequential Organ Failure Assessment (SOFA) score (AUROC 0.77 v/s 0.72; p = 0.02). These findings quantitatively confirm the prior understanding that the respiratory rate alone does not adequately represent the complexity of respiratory kinematics; they demonstrate that high-dimensional signatures of labored breathing can be quantified in routine practice settings, and they can improve predictions of clinical deterioration.

Sympathetic reinnervation in cardiac transplant recipients: Prevalence, time course, and association with long-term survival

BACKGROUND

Partial cardiac sympathetic reinnervation after cardiac transplant has been extensively investigated and evidenced. However, there have been no large-scale, long-term studies evaluating the prevalence, time-course, and association with long-term survival of sympathetic reinnervation of the heart.

METHODS

Cardiac transplant recipients (n = 232) were recruited from outpatient clinic at a single transplant center in the United Kingdom. Participants were each tested once for the presence of sympathetic reinnervation of the sinus node using the low-frequency component of power spectral analysis of heart rate variability, with a cutoff defined as 2 standard deviations above the mean for denervated participants (those tested <56 days posttransplant). Time course was calculated based on the timing of testing posttransplant. Patients were then followed up over a period of up to 27 years after transplant for survival analysis.

RESULTS

The overall prevalence of cardiac sympathetic reinnervation in the 225 patients tested >56 days posttransplant was 64.9%. Sympathetic reinnervation primarily occurred in the first 18 months after transplant, with a plateau thereafter. The prevalence in participants tested >18 months posttransplant was 69.6%. In Kaplan-Meier survival analysis, sympathetic reinnervation was associated with significantly improved survival (Log-rank p = 0.019), with a median survival time for reinnervated patients of 19.9 years compared with 14.4 years for the denervated group.

CONCLUSIONS

Sympathetic reinnervation of the sinus node occurs mostly within 18 months of transplant, is found in 70% of cardiac transplant recipients tested >18 months posttransplant, and is associated with significantly improved long-term survival.

Publication guidelines for human heart rate and heart rate variability studies in psychophysiology-Part 1: Physiological underpinnings and foundations of measurement

This Committee Report provides methodological, interpretive, and reporting guidance for researchers who use measures of heart rate (HR) and heart rate variability (HRV) in psychophysiological research. We provide brief summaries of best practices in measuring HR and HRV via electrocardiographic and photoplethysmographic signals in laboratory, field (ambulatory), and brain-imaging contexts to address research questions incorporating measures of HR and HRV. The Report emphasizes evidence for the strengths and weaknesses of different recording and derivation methods for measures of HR and HRV. Along with this guidance, the Report reviews what is known about the origin of the heartbeat and its neural control, including factors that produce and influence HRV metrics. The Report concludes with checklists to guide authors in study design and analysis considerations, as well as guidance on the reporting of key methodological details and characteristics of the samples under study. It is expected that rigorous and transparent recording and reporting of HR and HRV measures will strengthen inferences across the many applications of these metrics in psychophysiology. The prior Committee Reports on HR and HRV are several decades old. Since their appearance, technologies for human cardiac and vascular monitoring in laboratory and daily life (i.e., ambulatory) contexts have greatly expanded. This Committee Report was prepared for the Society for Psychophysiological Research to provide updated methodological and interpretive guidance, as well as to summarize best practices for reporting HR and HRV studies in humans.

Short-term heart rate variability: A potential approach to frailty assessment in older adults

Objectives

This study aimed to evaluate cardiac autonomic modulation using short-term heart rate variability (HRV) and compare it among frailty statuses in older Indian adults.

Methods

A total of 210 subjects aged 60 years and above were recruited into three groups: frail (n = 70), pre-frail (n = 70), and non-frail (n = 70) from the outpatient department of Geriatric Medicine at a tertiary care hospital in India. Frailty status was assessed using the Rockwood frailty index (FI) criteria. HRV was derived from a 5-min ECG recording of standard limb leads and assessed using time domain, frequency domain, and nonlinear analysis of cardiac interval variability.

Results

The HRV parameters indicative of parasympathetic modulation such as SDNN, SDSD, rMSSD, NN50, pNN50, absolute HF power, and SD1 were significantly lower in frail subjects compared with both pre-frail and non-frail subjects (P < 0.05). Absolute LF power and SD2 were also lower in frail subjects compared with pre-frail and non-frail subjects (P < 0.05). Measures of sympatho-vagal balance (LF/HF and SD1/SD2 ratios) did not show statistical significance. The FI demonstrated negative correlations with all HRV parameters.

Conclusions

Frail individuals exhibit decreased sympathetic and parasympathetic modulation compared with pre-frail and non-frail individuals, although maintaining a balanced sympatho-vagal state. Furthermore, autonomic modulation declines progressively with increasing frailty.

Multifractal Heart Rate Value Analysis: A Novel Approach for Diabetic Neuropathy Diagnosis

Type 2 diabetes mellitus (T2DM) is characterized by several complications, such as retinopathy, renal failure, cardiovascular disease, and diabetic neuropathy. Among these, neuropathy is the most severe complication, due to the challenging nature of its early detection. The linear Hearth Rate Variability (HRV) analysis is the most common diagnosis technique for diabetic neuropathy, and it is characterized by the determination of the sympathetic-parasympathetic balance on the peripheral nerves through a linear analysis of the tachogram obtained using photoplethysmography. We aimed to perform a multifractal analysis to identify autonomic neuropathy, which was not yet manifest and not detectable with the linear HRV analysis. We enrolled 10 healthy controls, 10 T2DM-diagnosed patients with not-full-blown neuropathy, and 10 T2DM diagnosed patients with full-blown neuropathy. The tachograms for the HRV analysis were obtained using finger photoplethysmography and a linear and/or multifractal analysis was performed. Our preliminary results showed that the linear analysis could effectively differentiate between healthy patients and T2DM patients with full-blown neuropathy; nevertheless, no differences were revealed comparing the full-blown to not-full-blown neuropathic diabetic patients. Conversely, the multifractal HRV analysis was effective for discriminating between full-blown and not-full-blown neuropathic T2DM patients. The multifractal analysis can represent a powerful strategy to determine neuropathic onset, even without clinical diagnostic evidence.

Game Fun Prediction Based on Frequency Domain Physiological Signals: Observational Study

Traditionally, the subjective questionnaire collected from game players is regarded as a primary tool to evaluate a video game. However, the subjective evaluation result may vary due to individual differences, and it is not easy to provide real-time feedback to optimize the user experience. This paper aims to develop an objective game fun prediction system. In this system, the wearables with photoplethysmography (PPG) sensors continuously measure the heartbeat signals of game players, and the frequency domain heart rate variability (HRV) parameters can be derived from the inter-beat interval (IBI) sequence. Frequency domain HRV parameters, such as low frequency(LF), high frequency(HF), and LF/HF ratio, highly correlate with the human's emotion and mental status. Most existing works on emotion measurement during a game adopt time domain physiological signals such as heart rate and facial electromyography (EMG). Time domain signals can be easily interfered with by noises and environmental effects. The main contributions of this paper include (1) regarding the curve transition and standard deviation of LF/HF ratio as the objective game fun indicators and (2) proposing a linear model using objective indicators for game fun score prediction. The self-built dataset in this study involves ten healthy participants, comprising 36 samples. According to the analytical results, the linear model's mean absolute error (MAE) was 4.16%, and the root mean square error (RMSE) was 5.07%. While integrating this prediction model with wearable-based HRV measurements, the proposed system can provide a solution to improve the user experience of video games.

McDAPS: A multi-channel physiological signals display and analysis system for clinical researchers

We introduce McDAPS, an interactive software for assessing autonomic imbalance from non-invasive multi-channel physiological recordings. McDAPS provides a graphical user interface for data visualization, beat-to-beat processing and interactive analyses. The software extracts beat-to-beat RR interval systolic blood pressure, diastolic blood pressure, the pulse amplitude of photoplethysmogram and the pulse-to-pulse interval. The analysis modules include stationary and time-varying power spectral analyses, moving-correlation analysis and univariate analyses. Analyses can also be performed in batch mode if multiple datasets have to be processed in the same way. The program exports results in standard CSV format. McDAPS runs in MATLAB, and is supported on MS Windows and MAC OS systems. The MATLAB source code is available at https://github.com/thuptimd/McDAPS.git.

Autonomic nervous system assessment using heart rate variability

The role of the autonomic nervous system in the onset of supraventricular and ventricular arrhythmias is well established. It can be analysed by the spontaneous behaviour of the heart rate with ambulatory ECG recordings, through heart rate variability measurements. Input of heart rate variability parameters into artificial intelligence models to make predictions regarding the detection or forecast of rhythm disorders is becoming routine and neuromodulation techniques are now increasingly used for their treatment. All this warrants a reappraisal of the use of heart rate variability for autonomic nervous system assessment.Measurements performed over long periods such as 24H-variance, total power, deceleration capacity, and turbulence are suitable for estimating the individual basal autonomic status. Spectral measurements performed over short periods provide information on the dynamics of systems that disrupt this basal balance and may be part of the triggers of arrhythmias, as well as premature atrial or ventricular beats. All heart rate variability measurements essentially reflect the modulations of the parasympathetic nervous system which are superimposed on the impulses of the adrenergic system. Although heart rate variability parameters have been shown to be useful for risk stratification in patients with myocardial infarction and patients with heart failure, they are not part of the criteria for prophylactic implantation of an intracardiac defibrillator, because of their high variability and the improved treatment of myocardial infarction. Graphical methods such as Poincaré plots allow quick screening of atrial fibrillation and are set to play an important role in the e-cardiology networks. Although mathematical and computational techniques allow manipulation of the ECG signal to extract information and permit their use in predictive models for individual cardiac risk stratification, their explicability remains difficult and making inferences about the activity of the ANS from these models must remain cautious.

Consensus for experimental design in electromyography (CEDE) project: Single motor unit matrix

The analysis of single motor unit (SMU) activity provides the foundation from which information about the neural strategies underlying the control of muscle force can be identified, due to the one-to-one association between the action potentials generated by an alpha motor neuron and those received by the innervated muscle fibers. Such a powerful assessment has been conventionally performed with invasive electrodes (i.e., intramuscular electromyography (EMG)), however, recent advances in signal processing techniques have enabled the identification of single motor unit (SMU) activity in high-density surface electromyography (HDsEMG) recordings. This matrix, developed by the Consensus for Experimental Design in Electromyography (CEDE) project, provides recommendations for the recording and analysis of SMU activity with both invasive (needle and fine-wire EMG) and non-invasive (HDsEMG) SMU identification methods, summarizing their advantages and disadvantages when used during different testing conditions. Recommendations for the analysis and reporting of discharge rate and peripheral (i.e., muscle fiber conduction velocity) SMU properties are also provided. The results of the Delphi process to reach consensus are contained in an appendix. This matrix is intended to help researchers to collect, report, and interpret SMU data in the context of both research and clinical applications.

Interactive Cardio System for Healthcare Improvement

The paper presents an interactive cardio system that can be used to improve healthcare. The proposed system receives, processes, and analyzes cardio data using an Internet-based software platform. The system enables the acquisition of biomedical data using various means of recording cardiac signals located in remote locations around the world. The recorded discretized cardio information is transmitted to the system for processing and mathematical analysis. At the same time, the recorded cardio data can also be stored online in established databases. The article presents the algorithms for the preprocessing and mathematical analysis of cardio data (heart rate variability). The results of studies conducted on the Holter recordings of healthy individuals and individuals with cardiovascular diseases are presented. The created system can be used for the remote monitoring of patients with chronic cardiovascular diseases or patients in remote settlements (where, for example, there may be no hospitals), control and assistance in the process of treatment, and monitoring the taking of prescribed drugs to help to improve people's quality of life. In addition, the issue of ensuring the security of cardio information and the confidentiality of the personal data of health users is considered.

Analysis of respiratory kinematics: a method to characterize breaths from motion signals

Breathing motion (respiratory kinematics) can be characterized by the interval and depth of each breath, and by magnitude-synchrony relationships between locations. Such characteristics and their breath-by-breath variability might be useful indicators of respiratory health. To enable breath-by-breath characterization of respiratory kinematics, we developed a method to detect breaths using motion sensors. In 34 volunteers who underwent maximal exercise testing, we used 8 motion sensors to record upper rib, lower rib and abdominal kinematics at 3 exercise stages (rest, lactate threshold and exhaustion). We recorded volumetric air flow signals using clinical exercise laboratory equipment and synchronized them with kinematic signals. Using instantaneous phase landmarks from the analytic representation of kinematic and flow signals, we identified individual breaths and derived respiratory rate (RR) signals at 1Hz. To evaluate the fidelity of kinematics-derived RR, we calculated bias, limits of agreement, and cross-correlation coefficients (CCC) relative to flow-derived RR. To identify coupling between kinematics and flow, we calculated the Shannon entropy of the relative frequency with which flow landmarks were distributed over the phase of the kinematic cycle. We found good agreement in the kinematics-derived and flow-derived RR signals [bias (95% limit of agreement) = 0.1 (± 7) breaths/minute; CCC median (IQR) = 0.80 (0.48 - 0.91)]. In individual signals, kinematics and flow were well-coupled (entropy 0.9-1.4 across sensors), but the relationship varied within (by exercise stage) and between individuals. The final result was that the flow landmarks did not consistently localize to any particular phase of the kinematic signals (entropy 2.2-3.0 across sensors). The Analysis of Respiratory Kinematics method can yield highly resolved respiratory rate signals by separating individual breaths. This method will facilitate characterization of clinically significant breathing motion patterns on a breath-by-breath basis. The relationship between respiratory kinematics and flow is much more complex than expected, varying between and within individuals.

Heart rate variability and the dawn of complex physiological signal analysis: methodological and clinical perspectives

Spontaneous beat-to-beat variations of heart rate (HR) have intrigued scientists and casual observers for centuries; however, it was not until the 1970s that investigators began to apply engineering tools to the analysis of these variations, fostering the field we now know as heart rate variability or HRV. Since then, the field has exploded to not only include a wide variety of traditional linear time and frequency domain applications for the HR signal, but also more complex linear models that include additional physiological parameters such as respiration, arterial blood pressure, central venous pressure and autonomic nerve signals. Most recently, the field has branched out to address the nonlinear components of many physiological processes, the complexity of the systems being studied and the important issue of specificity for when these tools are applied to individuals. When the impact of all these developments are combined, it seems likely that the field of HRV will soon begin to realize its potential as an important component of the toolbox used for diagnosis and therapy of patients in the clinic. This article is part of the theme issue 'Advanced computation in cardiovascular physiology: new challenges and opportunities'.

Vasoconstriction Response to Mental Stress in Sickle Cell Disease: The Role of the Cardiac and Vascular Baroreflexes

Recent studies have shown that individuals with sickle cell disease (SCD) exhibit greater vasoconstriction responses to physical autonomic stressors, such as heat pain and cold pain than normal individuals, but this is not the case for mental stress (MTS). We sought to determine whether this anomalous finding for MTS is related to inter-group differences in baseline cardiac and vascular autonomic function. Fifteen subjects with SCD and 15 healthy volunteers participated in three MTS tasks: N-back, Stroop, and pain anticipation (PA). R-R interval (RRI), arterial blood pressure and finger photoplethysmogram (PPG) were continuously monitored before and during these MTS tasks. The magnitude of vasoconstriction was quantified using change in PPG amplitude (PPGa) from the baseline period. To represent basal autonomic function, we assessed both cardiac and vascular arms of the baroreflex during the baseline period. Cardiac baroreflex sensitivity (BRSc) was estimated by applying both the "sequence" and "spectral" techniques to beat-to-beat measurements of systolic blood pressure and RRIs. The vascular baroreflex sensitivity (BRSv) was quantified using the same approaches, modified for application to beat-to-beat diastolic blood pressure and PPGa measurements. Baseline BRSc was not different between SCD and non-SCD subjects, was not correlated with BRSv, and was not associated with the vasoconstriction responses to MTS tasks. BRSv in both groups was correlated with mean PPGa, and since both baseline PPGa and BRSv were lower in SCD, these results suggested that the SCD subjects were in a basal state of higher sympathetically mediated vascular tone. In both groups, baseline BRSv was positively correlated with the vasoconstriction responses to N-back, Stroop, and PA. After adjusting for differences in BRSv within and between groups, we found no difference in the vasoconstriction responses to all three mental tasks between SCD and non-SCD subjects. The implications of these findings are significant in subjects with SCD since vasoconstriction reduces microvascular flow and prolongs capillary transit time, increasing the likelihood for vaso-occlusive crisis (VOC) to be triggered by exposure to stressful events.

Reducing Motion Artifacts of Pulse Intervals from Photoplethysmogram of a Commercial Wristband for Heart Rate Variability Analysis

Heart rate monitoring based on photoplethysmography (PPG) is a noninvasive and inexpensive way of measuring many important cardiovascular metrics such as heart rate and heart rate variability, and has been used in many wearable devices. Unfortunately, the accuracy of the measurements is compromised by motion artifacts. We propose a theoretically sound method to reduce the motion artifacts of heart rate sensed by a commercial wristband. This method is based on outlier detection and singular spectrum analysis which enables us to reduce the movement-related noise in non-stationary signals. The results suggest that this method exhibits high correspondence to the simultaneously measured heart rate using ECG. Several metrics of heart rate variability computed from cleaned data also indicate high agreement with those obtained from ECG.

Interactive Effects of Heart Rate Variability and P-QRS-T on the Power Density Spectra of ECG Signals

Different from the traditional methods of assessing the cardiac activities through heart rhythm statistics or P-QRS-T complexes separately, this study demonstrates their interactive effects on the power density spectrum (PDS) of ECG signal with applications for the diagnosis of ST-segment elevation myocardial infarction (STEMI) diseases. Firstly, a mathematical model of the PDS of ECG signal with a random pacing pulse train (PPT) mimicking S-A node firings was derived. Secondly, an experimental PDS analysis was performed on clinical ECG signals from 49 STEMI patients and 42 healthy subjects in PTB Diagnostic Database. It was found that besides the interactive effects which are consistent between theoretical and experimental results, the ECG PDSs of STEMI patients exhibited consistently significant power shift towards lower frequency range in ST-elevated leads in comparison with those of reference leads and leads of health subjects with the highest median frequency shift ratios at 51.39 12.94% found in anterior MI. Thirdly, the results of ECG simulation with systematic changes in PPT firing statistics over various lengths of ECG data ranging from 10s to 60 mins revealed that the mean and median frequency parameters were less affected by the heart rhythm statistics and the data length but more depended on the alterations of P-QRS-T complexes, which were further confirmed on 33 more STEMI patients in European ST-T Database, demonstrating that the frequency indexes could be potentially used as alternative indicators for STEMI diagnosis even with ultra-short-term ECG recordings suitable for wearable and mobile health applications in living-free environments.

Identifying elevated risk for future pain crises in sickle-cell disease using photoplethysmogram patterns measured during sleep: A machine learning approach

Transient increases in peripheral vasoconstriction frequently occur in obstructive sleep apnea and periodic leg movement disorder, both of which are common in sickle cell disease (SCD). These events reduce microvascular blood flow and increase the likelihood of triggering painful vaso-occlusive crises (VOC) that are the hallmark of SCD. We recently reported a significant association between the magnitude of vasoconstriction, inferred from the finger photoplethysmogram (PPG) during sleep, and the frequency of future VOC in 212 children with SCD. In this study, we present an improved predictive model of VOC frequency by employing a two-level stacking machine learning (ML) model that incorporates detailed features extracted from the PPG signals in the same database. The first level contains seven different base ML algorithms predicting each subject's pain category based on the input PPG characteristics and other clinical information, while the second level is a meta model which uses the inputs to the first-level model along with the outputs of the base models to produce the final prediction. Model performance in predicting future VOC was significantly higher than in predicting VOC prior to each sleep study (F1-score of 0.43 vs. 0.35, p-value <0.0001), consistent with our hypothesis of a causal relationship between vasoconstriction and future pain incidence, rather than past pain leading to greater propensity for vasoconstriction. The model also performed much better than our previous conventional statistical model (F1 = 0.33), as well as all other algorithms that used only the base-models for predicting VOC without the second tier meta model. The modest F1 score of the present predictive model was due in part to the relatively small database with substantial imbalance (176:36) between low-pain and high-pain subjects, as well as other factors not captured by the sleep data alone. This report represents the first attempt ever to use non-invasive finger PPG measurements during sleep and a ML-based approach to predict increased propensity for VOC crises in SCD. The promising results suggest the future possibility of embedding an improved version of this model in a low-cost wearable system to assist clinicians in managing long-term therapy for SCD patients.

How to Use Heart Rate Variability: Quantification of Vagal Activity in Toddlers and Adults in Long-Term ECG

Recent developments in noninvasive electrocardiogram (ECG) monitoring with small, wearable sensors open the opportunity to record high-quality ECG over many hours in an easy and non-burdening way. However, while their recording has been tremendously simplified, the interpretation of heart rate variability (HRV) data is a more delicate matter. The aim of this paper is to supply detailed methodological discussion and new data material in order to provide a helpful notice of HRV monitoring issues depending on recording conditions and study populations. Special consideration is given to the monitoring over long periods, across periods with different levels of activity, and in adults versus children. Specifically, the paper aims at making users aware of neglected methodological limitations and at providing substantiated recommendations for the selection of appropriate HRV variables and their interpretation. To this end, 30-h HRV data of 48 healthy adults (18–40 years) and 47 healthy toddlers (16–37 months) were analyzed in detail. Time-domain, frequency-domain, and nonlinear HRV variables were calculated after strict signal preprocessing, using six different high-frequency band definitions including frequency bands dynamically adjusted for the individual respiration rate. The major conclusion of the in-depth analyses is that for most applications that implicate long-term monitoring across varying circumstances and activity levels in healthy individuals, the time-domain variables are adequate to gain an impression of an individual’s HRV and, thus, the dynamic adaptation of an organism’s behavior in response to the ever-changing demands of daily life. The sound selection and interpretation of frequency-domain variables requires considerably more consideration of physiological and mathematical principles. For those who prefer using frequency-domain variables, the paper provides detailed guidance and recommendations for the definition of appropriate frequency bands in compliance with their specific recording conditions and study populations.

EWS-FLI1-mediated tenascin-C expression promotes tumour progression by targeting MALAT1 through integrin α5β1-mediated YAP activation in Ewing sarcoma

BACKGROUND

The extracellular matrix has been critically associated with the tumorigenesis and progression of Ewing sarcoma (ES). However, the regulatory and prognostic roles of tenascin-C (TNC) in ES remain unclear.

METHODS

TNC expression was examined in specimens by immunohistochemistry, and the association of TNC expression with ES patient survival was also analysed. TNC-knockout cell lines were constructed using CRISPR/Cas9 methods. In vitro experiments and in vivo bioluminescent imaging using BALB/c nude mice were conducted to evaluate the effect of TNC on ES tumour progression. RNA sequencing was performed, and the underlying mechanism of TNC was further explored.

RESULTS

TNC was overexpressed in ES tissue and cell lines, and TNC overexpression was associated with poor survival in ES patients. TNC enhanced cell proliferation, migration and angiogenesis in vitro and promoted ES metastasis in vivo. The oncoprotein EWS-FLI1 profoundly increased TNC expression by directly binding to the TNC promoter region. Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) upregulation induced by Yes-associated protein (YAP) activation was responsible for TNC-regulated ES tumour progression. Activated integrin α5β1 signalling might be correlated with YAP dephosphorylation and nuclear translocation.

CONCLUSIONS

TNC may promote ES tumour progression by targeting MALAT1 through integrin α5β1-mediated YAP activation.

Introduction of Application of Gini Coefficient to Heart Rate Variability Spectrum for Mental Stress Evaluation

Background

The Gini coefficient is a statistical tool generally used by economists to quantify income inequality. However, it can be applied to any kind of data with unequal distribution, including heart rate variability (HRV).

Objectives

To assess the application of the Gini coefficient to measure inequality in power spectral density of RR intervals, and to use this application as a psychophysiological indicator of mental stress.

Methods

Thirteen healthy subjects (19 ± 1.5 years) participated in this study, and their RR intervals were obtained by electrocardiogram during rest (five minutes) and during mental stress (arithmetic challenge; five minutes). These RR intervals were used to obtain the estimates of power spectral densities (PSD). The limits for the PSD bands were defined from 0.15 to 0.40 Hz for high frequency band (HF), from 0.04 to 0.15 Hz for low frequency band (LF), from 0.04 to 0.085 Hz for first low frequency sub-band (LF1) and from 0.085 to 0.15 Hz for second low frequency sub-band (LF2). The spectral Gini coefficient (SpG) was proposed to measure the inequality in the power distribution of the RR intervals in each of above-mentioned HRV bands. SpG from each band was compared with its respective traditional index of HRV during the conditions of rest and mental stress. All the differences were considered statistically significant for p < 0.05.

Results

There was a significant decrease in HF power (p = 0.046), as well as significant increases in heart rate (p = 0.004), LF power (p = 0.033), LF2 power (p = 0.019) and LF/HF (p = 0.002) during mental stress. There was also a significant increase in SpG(LF) (p = 0.009) and SpG(LF2) (p = 0.033) during mental stress. Coefficient of variation showed SpG has more homogeneity compared to the traditional index of HRV during mental stress.

Conclusions

This pilot study suggested that spectral inequality of Heart Rate Variability analyzed using the Gini coefficient seems to be an independent and homogeneous psychophysiological indicator of mental stress. Also, HR, LF/HF, SpG(LF) of HRV are possibly important, reliable and valid indicators of mental stress.

CRSIDLab: A Toolbox for Multivariate Autonomic Nervous System Analysis Using Cardiorespiratory Identification

This paper presents the Cardiorespiratory System Identification Lab (CRSIDLab), a MATLAB-based software tool for multivariate autonomic nervous system (ANS) evaluation through heart rate variability (HRV) analysis and cardiorespiratory system identification. Based on a graphical user interface, CRSIDLab provides a complete set of tools including pre-processing cardiorespiratory data (electrocardiogram, continuous blood pressure, airflow, and instantaneous lung volume), power spectral density estimation, and multivariable cardiorespiratory system model identification. Parametrized multivariate models can assess both HRV and baroreflex sensitivity (BRS) by considering the causal relationship from respiration to heart rate (or its reciprocal, R-to-R interval - RRI) and from systolic blood pressure to RRI, for instance. The impulse response, estimated from the model, is used as a mathematical tool to effectively open the inherently closed-loop nature of the cardiorespiratory system, allowing the investigation of the dynamic response between pairs of cardiorespiratory variables. This system modeling approach provides information on gain and temporal behavior regarding dynamics, such as the baroreflex, complementing traditional HRV, and BRS indices. The toolbox is presented and used to investigate autonomic function in sleep apnea. The results show that, while traditional HRV indices were unable to differentiate between apneic and non-apneic subjects, the autonomic descriptors obtained from the multivariate system identification techniques were able to show vagal impairment in apneic compared to non-apneic subjects. Thus, CRSIDLab can help promote the use of cardiorespiratory system identification as a potentially more sensitive measure of ANS activity than classical HRV analysis.

Sickle Cell Disease Subjects Have a Distinct Abnormal Autonomic Phenotype Characterized by Peripheral Vasoconstriction With Blunted Cardiac Response to Head-Up Tilt

In sickle cell disease (SCD), prolonged capillary transit times, resulting from reduced peripheral blood flow, increase the likelihood of rigid red cells entrapment in the microvasculature, predisposing to vaso-occlusive crisis. Since changes in peripheral flow are mediated by the autonomic nervous system (ANS), we tested the hypothesis that the cardiac and peripheral vascular responses to head-up tilt (HUT) are abnormal in SCD. Heart rate, respiration, non-invasive continuous blood pressure and finger photoplethysmogram (PPG) were monitored before, during, and after HUT in SCD, anemic controls and healthy subjects. Percent increase in heart rate from baseline was used to quantify cardiac ANS response, while percent decrease in PPG amplitude represented degree of peripheral vasoconstriction. After employing cluster analysis to determine threshold levels, the HUT responses were classified into four phenotypes: (CP) increased heart rate and peripheral vasoconstriction; (C) increased heart rate only; (P) peripheral vasoconstriction only; and (ST) subthreshold cardiac and peripheral vascular responses. Multinomial logistic regression (MLR) was used to relate these phenotypic responses to various parameters representing blood properties and baseline cardiovascular activity. The most common phenotypic response, CP, was found in 82% of non-SCD subjects, including those with chronic anemia. In contrast, 70% of SCD subjects responded abnormally to HUT: C-phenotype = 22%, P-phenotype = 37%, or ST-phenotype = 11%. MLR revealed that the HUT phenotypes were significantly associated with baseline cardiac parasympathetic activity, baseline peripheral vascular variability, hemoglobin level and SCD diagnosis. Low parasympathetic activity at baseline dramatically increased the probability of belonging to the P-phenotype in SCD subjects, even after adjusting for hemoglobin level, suggesting a characteristic autonomic dysfunction that is independent of anemia. Further analysis using a mathematical model of heart rate variability revealed that the low parasympathetic activity in P-phenotype SCD subjects was due to impaired respiratory-cardiac coupling rather than reduced cardiac baroreflex sensitivity. By having strong peripheral vasoconstriction without compensatory cardiac responses, P-phenotype subjects may be at increased risk for vaso-occlusive crisis. The classification of autonomic phenotypes based on HUT response may have potential use for guiding therapeutic interventions to alleviate the risk of adverse outcomes in SCD.

Head-motion Robust Video-based Heart Rate Estimation Using Facial Feature Point Fluctuations

Interest in measuring heart rates (HRs) without physical contact has increased in the area of stress checking and health care. In this paper, we propose head-motion robust video-based heart rate estimation using facial feature point fluctuations. The proposed method adaptively estimates and removes such rigid-noise components as noise stemming from horizontal head motion and extracts relatively small heart signals. Rigid-noise components can be accurately estimated and removed by using changes in facial feature points which are not dominant over heart signals and are more dominant over noise signals than are such luminance signals as RGB. In evaluation experiments on a benchmark dataset, our method achieved the highest accuracy among state-of-the-art methods.

Autonomic Nervous Function and Blood Volume Monitoring during Hemodialysis

We studied the autonomic reflex response to hypovolemia during HD by means of spectral analysis of heart rate variability (SAHRV) in 10 hypotension prone (group A) and 10 hemodynamically stable patients (group B). UF rate normalized per total body water and blood volume fall were similar in the two groups. The sympatho-vagal balance index, calculated as the ratio between the integrals of the spectrum in the low (0.02-0.15 Hz) and in the high frequency range (0.2-0.35 Hz) rose in group B progressively from the beginning of the treatments, reaching a top at the 90th minute and remained subsequently high until the end. On the contrary this index did not show remarkable increases in group A. The differences between the two groups were statistically significant at 0 (4.6∓2.9 vs 1.5∓1.3), 60th (8.3+7.8 vs 2.2+2.6), 90th (17.9+13.4 vs 3.7+2.8), 150th (8.8+3.7 vs 2.7+2.8) and 210th minute (8.6+5.0 vs 2.9+2.5). In conclusion SAHRV shows an impairment of autonomic reflex response to hypovolemia in hypotension-prone patients.

Effect of Shallow and Deep SCUBA Dives on Heart Rate Variability

Prolonged and high pressure diving may lead to various physiological changes including significant alterations of autonomic nervous system (ANS) activity that may be associated with altered physical performance, decompression sickness, or central nervous system oxygen toxicity. Ideally, researchers could elucidate ANS function before, during, and after dives that are most associated with altered function and adverse outcomes. However, we have a limited understanding of the activities of the ANS especially during deeper prolonged SCUBA diving because there has never been a convenient way to collect physiological data during deep dives. This work is one of the first studies which was able to collect electrocardiogram (ECG) data from SCUBA divers at various depths (33, 66, 99, 150, and 200 ftsw; equivalent to 10.05, 20.10, 30.17, 45.72, and 60.96 m of salt water, respectively) breathing different gas mixtures (air, nitrox and trimix). The aim of this study was to shed light on cardiac ANS behavior during dives, including deep dives. With the aid of dry suits, a Holter monitor that could handle the pressure of a 200 ft. dive, and a novel algorithm that can provide a useful assessment of the ANS from the ECG signal, we investigated the effects of SCUBA dives with different time durations, depths and gas mixtures on the ANS. Principal dynamic mode (PDM) analysis of the ECG, which has been shown to provide accurate separation of the sympathetic and parasympathetic dynamics, was employed to assess the difference of ANS behavior between baseline and diving conditions of varying depths and gas mixtures consisting of air, nitrox and trimix. For all depths and gas mixtures, we found consistent dominance in the parasympathetic activity and a concomitant increase of the parasympathetic dynamics with increasing diving duration and depth. For 33 and 66 ft. dives, we consistently found significant decreases in heart rates (HR) and concomitant increases in parasympathetic activities as estimated via the PDM and root mean square of successive differences (RMSSD) for all time intervals (from the first 5 min to the last 30 min) at the bottom depth when compared to the baseline depth at sea level. The sympathetic dynamics did not change with dive duration or gas mixtures, but at the 150 and 200 ft. dives, we found a significant increase in the sympathetic dynamics in addition to the elevated parasympathetic dynamics when compared to baseline The power spectral density (PSD) measures such as the low frequency (LF), high frequency (HF) and its ratio, and approximate entropy (ApEn) indices were not as consistent when compared to PDM-derived parasympathetic dynamics and RMSSD index.

Very High Frequency Oscillations of Heart Rate Variability in Healthy Humans and in Patients with Cardiovascular Autonomic Neuropathy

Literature reports on the very high frequency (VHF) range of 0.4-0.9 Hz in heart rate variability (HRV) are scanty. The VHF presence in cardiac transplant patients and other conditions associated with reduced vagal influence on the heart encouraged us to explore this spectral band in healthy subjects and in patients diagnosed with cardiac autonomic neuropathy (CAN), and to assess the potential clinical value of some VHF indices. The study included 80 healthy controls and 48 patients with spinocerebellar ataxia type 2 (SCA2) with CAN. The electrocardiographic recordings of short 5-min duration were submitted to three different spectral analysis methods, including the most generally accepted procedure, and the two novel methods using the Hilbert-Huang transform. We demonstrated the presence of VHF activity in both groups of subjects. However, VHF power spectral density, expressed in relative normalized units, was significantly greater in the SCA2 patients than that in healthy subjects, amounting to 36.1 ± 17.4% vs. 22.9 ± 14.1%, respectively, as also was the instantaneous VHF spectral frequency, 0.58 ± 0.05 vs. 0.64 ± 0.07 Hz, respectively. These findings were related to the severity of CAN. We conclude that VHF activity of HRV is integral to the cardiovascular autonomic control.

Assessing Pain Intensity Using Photoplethysmography Signals in Chronic Myofascial Pain Syndrome

BACKGROUND

Efficacy of pain assessment is the basis for effective therapy. Clinically, assessing pain is by subjective scale, but these methods have some shortcomings. Therefore, studies have been conducted on assessment of pain using physiological signals. Photoplethysmography (PPG) signals provide much information about the cardiovascular system. PPG-derived parameters (PPG parameters) reflect nociceptive stimulation, and obtain an approximation of the R-R interval from the PPG period. The aim of this study was to evaluate PPG signals for assessment of pain intensity in chronic myofascial pain syndrome (MPS) patients.

METHODS

This study recruited 37 patients with chronic MPS; all of them were treated with electrotherapy and thermotherapy. The difference between pre- and post-therapy PPG parameters, and the correlation between pulse rate variability (PRV) and heart rate variability (HRV) were determined. We also obtained patients' pain intensity scores by visual analog scale, visual rating scale, and Wong-Banker face pain rating scale.

RESULTS

Photoplethysmography and PRV/HRV parameters showed significant differences between pre- and post-treatment. The variation trend of PRV was similar with HRV in heart rate, R-R interval, low frequency, high frequency, and LF/HF; in addition, a high correlation between the parameters was observed either in pre- or post-therapy. PPG parameters indicated increased sympathetic tone.

CONCLUSION

The results of the study indicated that PRV substituted for HRV in assessment of pain intensity in chronic MPS reflected parasympathetic nervous tone increase, and PPG parameters might reflect stress stimulation on skin.

HRV-derived data similarity and distribution index based on ensemble neural network for measuring depth of anaesthesia

Evaluation of depth of anaesthesia (DoA) is critical in clinical surgery. Indices derived from electroencephalogram (EEG) are currently widely used to quantify DoA. However, there are known to be inaccurate under certain conditions; therefore, experienced anaesthesiologists rely on the monitoring of vital signs such as body temperature, pulse rate, respiration rate, and blood pressure to control the procedure. Because of the lack of an ideal approach for quantifying level of consciousness, studies have been conducted to develop improved methods of measuring DoA. In this study, a short-term index known as the similarity and distribution index (SDI) is proposed. The SDI is generated using heart rate variability (HRV) in the time domain and is based on observations of data distribution differences between two consecutive 32 s HRV data segments. A comparison between SDI results and expert assessments of consciousness level revealed that the SDI has strong correlation with anaesthetic depth. To optimise the effect, artificial neural network (ANN) models were constructed to fit the SDI, and ANN blind cross-validation was conducted to overcome random errors and overfitting problems. An ensemble ANN was then employed and was discovered to provide favourable DoA assessment in comparison with commonly used Bispectral Index. This study demonstrated the effectiveness of this method of DoA assessment, and the results imply that it is feasible and meaningful to use the SDI to measure DoA with the additional use of other measurement methods, if appropriate.

Breathing Rate Estimation From the Electrocardiogram and Photoplethysmogram: A Review

Breathing rate (BR) is a key physiological parameter used in a range of clinical settings. Despite its diagnostic and prognostic value, it is still widely measured by counting breaths manually. A plethora of algorithms have been proposed to estimate BR from the electrocardiogram (ECG) and pulse oximetry (photoplethysmogram, PPG) signals. These BR algorithms provide opportunity for automated, electronic, and unobtrusive measurement of BR in both healthcare and fitness monitoring. This paper presents a review of the literature on BR estimation from the ECG and PPG. First, the structure of BR algorithms and the mathematical techniques used at each stage are described. Second, the experimental methodologies that have been used to assess the performance of BR algorithms are reviewed, and a methodological framework for the assessment of BR algorithms is presented. Third, we outline the most pressing directions for future research, including the steps required to use BR algorithms in wearable sensors, remote video monitoring, and clinical practice.

Observing continuous change in heart rate variability and photoplethysmography-derived parameters during the process of pain production/relief with thermal stimuli

Continuously monitoring and efficiently managing pain has become an important issue. However, no study has investigated a change in physiological parameters during the process of pain production/relief. This study modeled the process of pain production/relief using ramped thermal stimulation (no pain: 37°C water, process of pain production: a heating rate of 1°C/min, and subject feels pain: water kept at the painful temperature for each subject, with each segment lasting 10 min). In this duration, the variation of the heat rate variability and photoplethysmography-derived parameters was observed. A total of 40 healthy individuals participated: 30 in the trial group (14 males and 16 females with a mean age of 22.5±1.9 years) and 10 in the control group (7 males and 3 females with a mean age of 22.5±1.3 years). The results showed that the numeric rating scale value was 5.03±1.99 when the subjects felt pain, with a temperature of 43.54±1.70°C. Heart rate, R-R interval, low frequency, high frequency, photoplethysmography amplitude, baseline, and autonomic nervous system state showed significant changes during the pain production process, but these changes differed during the period Segment D (painful temperature 10: min). In summary, the study observed that physiological parameters changed qualitatively during the process of pain production and relief and found that the high frequency, low frequency, and photoplethysmography parameters seemed to have different responses in four situations (no pain, pain production, pain experienced, and pain relief). The trends of these variations may be used as references in the clinical setting for continuously observing pain intensity.

Guanfacine alters the effect of stress and smoking on heart rate variability in regular daily smokers

BACKGROUND

We had previously demonstrated that guanfacine, an α2a-adrenergic agonist, attenuated the effect of stress on smoking-lapse behavior in regular daily smokers. Heart rate variability (HRV), a measure of vagal activity, may be a potential mechanism underlying the relationship between stress, smoking, and relapse.

METHODS

We examined whether guanfacine (0 mg/day vs. 3 mg/day; n = 26) altered changes in high-frequency heart rate variability (HF-HRV) following stress and ad-lib smoking using a validated laboratory analogue of smoking-lapse behavior. All participants completed a parent study evaluating the effects of guanfacine on stress-precipitated smoking. Each subject completed two laboratory sessions assessing the effects of guanfacine on HF-HRV following stress imagery (vs. neutral imagery; order counterbalanced) and smoking.

RESULTS

Results demonstrated that guanfacine did not increase tonic levels of HF-HRV relative to placebo. Following the stress versus neutral imagery manipulation (prior to ad-lib smoking), there were no significant changes in HF-HRV in the placebo group. In contrast, guanfacine increased phasic HF-HRV following stress imagery and decreased HF-HRV following neutral imagery. Ad libitum smoking following both the stress and neutral conditions decreased HF-HRV in the placebo group across both imagery conditions. In contrast, guanfacine attenuated stress- and smoking-related decreases in phasic HF-HRV relative to the neutral imagery condition.

CONCLUSIONS

This is the first demonstration that a noradrenergic target altered dynamic changes in HF-HRV in response to stress and smoking, suggesting that guanfacine alters HF-HRV response to stress. Findings support current theories which suggest that phasic changes in HRV are an important marker of the stress response.

High-density Electroencephalographic Acquisition in a Rodent Model Using Low-cost and Open-source Resources

Advanced electroencephalographic analysis techniques requiring high spatial resolution, including electrical source imaging and measures of network connectivity, are applicable to an expanding variety of questions in neuroscience. Performing these kinds of analyses in a rodent model requires higher electrode density than traditional screw electrodes can accomplish. While higher-density electroencephalographic montages for rodents exist, they are of limited availability to most researchers, are not robust enough for repeated experiments over an extended period of time, or are limited to use in anesthetized rodents.^1-3 A proposed low-cost method for constructing a durable, high-count, transcranial electrode array, consisting of bilaterally implantable headpieces is investigated as a means to perform advanced electroencephalogram analyses in mice or rats.

Procedures for headpiece fabrication and surgical implantation necessary to produce high signal to noise, low-impedance electroencephalographic and electromyographic signals are presented. While the methodology is useful in both rats and mice, this manuscript focuses on the more challenging implementation for the smaller mouse skull. Freely moving mice are only tethered to cables via a common adapter during recording. One version of this electrode system that includes 26 electroencephalographic channels and 4 electromyographic channels is described below.

Comparison of methods for estimating motor unit firing rate time series from firing times

The central nervous system regulates recruitment and firing of motor units to modulate muscle tension. Estimation of the firing rate time series is typically performed by decomposing the electromyogram (EMG) into its constituent firing times, then lowpass filtering a constituent train of impulses. Little research has examined the performance of different estimation methods, particularly in the inevitable presence of decomposition errors. The study of electrocardiogram (ECG) and electroneurogram (ENG) firing rate time series presents a similar problem, and has applied novel simulation models and firing rate estimators. Herein, we adapted an ENG/ECG simulation model to generate realistic EMG firing times derived from known rates, and assessed various firing rate time series estimation methods. ENG/ECG-inspired rate estimation worked exceptionally well when EMG decomposition errors were absent, but degraded unacceptably with decomposition error rates of ⩾1%. Typical EMG decomposition error rates-even after expert manual review-are 3-5%. At realistic decomposition error rates, more traditional EMG smoothing approaches performed best, when optimal smoothing window durations were selected. This optimal window was often longer than the 400ms duration that is commonly used in the literature. The optimal duration decreased as the modulation frequency of firing rate increased, average firing rate increased and decomposition errors decreased. Examples of these rate estimation methods on physiologic data are also provided, demonstrating their influence on measures computed from the firing rate estimate.

Autonomic and peripheral nervous system function in acute tick-borne encephalitis

OBJECTIVES

Tick-borne encephalitis (TBE) is an emerging flaviviral zoonosis in Central and Eastern Europe. TBE can present as meningitis, meningoencephalitis, or meningoencephalomyelitis. Dysfunction of the autonomic (ANS) and peripheral motoric and sensory nervous system (PNS) might contribute to acute and long-term complications. We aimed to examine, whether the ANS and PNS are affected in acute TBE.

METHODS

Fourteen patients with acute TBE, 17 with diabetic polyneuropathy (d-PNP), and 30 healthy controls (HC) were examined in our single-center, prospective study. ANS and PNS function was assessed by time- and frequency-domain parameters of the heart rate (HR) variability at rest and deep respiration, and by sural and tibial nerve neurography. Primary endpoint was the HR variability at rest measured by root mean square of the successive differences (RMSSD). Autonomic symptoms and quality of life (QoL) were assessed by questionnaires.

RESULTS

Tick-borne encephalitis patients had a lower RMSSD at rest (TBE 13.1 ± 7.0, HC 72.7 ± 48.3; P < 0.001) and deep respiration (TBE 42.8 ± 27.0, HC 109.7 ± 68.8; P < 0.01), an increased low-frequency to high-frequency power component ratio at rest (TBE 4.0 ± 4.0, HC 0.8 ± 0.5; P < 0.001), and a higher minimal heart rate at rest (TBE 85.4 ± 7.0, HC 69.5 ± 8.5; P < 0.001), all similar to patients with d-PNP, indicating sympathovagal imbalance with increased sympathetic activation. Compared to HC, sural and tibial nerve conduction velocities and action potential amplitudes were reduced, ANS symptoms were more frequent, and QoL was lower in patients with TBE.

CONCLUSIONS

The ANS and to a lesser degree the PNS are affected by acute TBE, which could potentially contribute to short- and long-term morbidity.

A Robust System for Longitudinal Knee Joint Edema and Blood Flow Assessment Based on Vector Bioimpedance Measurements

We present a robust vector bioimpedance measurement system for longitudinal knee joint health assessment, capable of acquiring high resolution static (slowly varying over the course of hours to days) and dynamic (rapidly varying on the order of milli-seconds) bioresistance and bioreactance signals. Occupying an area of 78×90 mm(2) and consuming 0.25 W when supplied with ±5 V, the front-end achieves a dynamic range of 345 Ω and noise floor of 0.018 mΩrms (resistive) and 0.055 mΩrms (reactive) within a bandwidth of 0.1-20 Hz. A microcontroller allows real-time calibration to minimize errors due to environmental variability (e.g., temperature) that can be experienced outside of lab environments, and enables data storage on a micro secure digital card. The acquired signals are then processed using customized physiology-driven algorithms to extract musculoskeletal (edema) and cardiovascular (local blood volume pulse) features from the knee joint. In a feasibility study, we found statistically significant differences between the injured and contralateral static knee impedance measures for two subjects with recent unilateral knee injury compared to seven controls. Specifically, the impedance was lower for the injured knees, supporting the physiological expectations for increased edema and damaged cell membranes. In a second feasibility study, we demonstrate the sensitivity of the dynamic impedance measures with a cold-pressor test, with a 20 mΩ decrease in the pulsatile resistance associated with increased downstream peripheral vascular resistance. The proposed system will serve as a foundation for future efforts aimed at quantifying joint health status continuously during normal daily life.

Autonomic Neuropathy and Endothelial Dysfunction in Patients With Impaired Glucose Tolerance or Type 2 Diabetes Mellitus

Autonomic neuropathy is one of the most common complications of diabetes mellitus (DM). The etiology of autonomic impairment is not well-understood, yet. There is need for studies to investigate the cause-effect relationships of inflammation and/or endothelial dysfunction and diabetic autonomic neuropathy. Only a few reports have mentioned autonomic neuropathy in individuals with impaired glucose tolerance (IGT), previously. Furthermore, the association between the plasma markers of endothelial dysfunction (von Willebrand factor (vWF), soluble E-selectin) and autonomic neuropathy in patients with IGT or DM has not been studied before. In this study, we aimed to investigate the correlation between plasma markers of endothelial dysfunction and autonomic neuropathy in patients with IGT or type 2 DM (T2DM).In this case-control study, 25 IGT patients, 25 T2DM patients with autonomic symptoms, and 30 controls were included. Demographical data, HbA1c, vWF, and soluble E-selectin (sE-selectin) levels were analyzed. Sympathetic skin response (SSR) and heart rate variability (HRV) were used as the indicator of autonomic activity.Plasma levels of HbA1c, vWF, and sE-selectin were higher in patients with IGT than the controls; patients with T2DM had higher levels than both the controls and the patients with IGT. SSR measures were similar among the groups. However, higher number of T2DM patients had absent plantar SSR than controls. HRV analysis at rest revealed lower standard deviation of R-R interval, coefficient of variation of R-R interval, low-frequency (LF) power and total power in patients with IGT and T2DM than the controls. In addition, HRV analysis at deep breathing showed lower high-frequency (HF) power in IGT group. LF:HF ratio was lower in both patient groups at rest. No strong correlation was found between the levels of HbA1c, vWF, sE-selectin, HRV, and SSR measures.Our results support that endothelial dysfunction is evident in individuals with IGT or T2DM and HRV is impaired in early stages in the course of T2DM. However, increased levels of biomarkers of endothelial damage do not correlate with HRV or SSR. More studies are needed to clarify the disease pathogenesis and its clinical correlates. Impaired HRV in T2DM could be due to mechanisms other than endothelial dysfunction.

Spectral Heart Rate Variability analysis using the heart timing signal for the screening of the Sleep Apnea-Hypopnea Syndrome

Some approaches have been published in the past using Heart Rate Variability (HRV) spectral features for the screening of Sleep Apnea-Hypopnea Syndrome (SAHS) patients. However there is a big variability among these methods regarding the selection of the source signal and the specific spectral components relevant to the analysis. In this study we investigate the use of the Heart Timing (HT) as the source signal in comparison to the classical approaches of Heart Rate (HR) and Heart Period (HP). This signal has the theoretical advantage of being optimal under the Integral Pulse Frequency Modulation (IPFM) model assumption. Only spectral bands defined as standard for the study of HRV are considered, and for each method the so-called LF/HF and VLFn features are derived. A comparative statistical analysis between the different resulting methods is performed, and subject classification is investigated by means of ROC analysis and a Naïve-Bayes classifier. The standard Apnea-ECG database is used for validation purposes. Our results show statistical differences between SAHS patients and controls for all the derived features. In the subject classification task the best performance in the testing set was obtained using the LF/HF ratio derived from the HR signal (Area under ROC curve=0.88). Only slight differences are obtained due to the effect of changing the source signal. The impact of using the HT signal in this domain is therefore limited, and has not shown relevant differences with respect to the use of the classical approaches of HR or HP.

Design of tree structured matched wavelet for HRV signals of menstrual cycle

An algorithm is presented for designing a new class of wavelets matched to the Heart Rate Variability (HRV) signals of the menstrual cycle. The proposed wavelets are used to find HRV variations between phases of menstrual cycle. The method finds the signal matching characteristics by minimising the shape feature error using Least Mean Square method. The proposed filter banks are used for the decomposition of the HRV signal. For reconstructing the original signal, the tree structure method is used. In this approach, decomposed sub-bands are selected based upon their energy in each sub-band. Thus, instead of using all sub-bands for reconstruction, sub-bands having high energy content are used for the reconstruction of signal. Thus, a lower number of sub-bands are required for reconstruction of the original signal which shows the effectiveness of newly created filter coefficients. Results show that proposed wavelets are able to differentiate HRV variations between phases of the menstrual cycle accurately than standard wavelets.

Effect of Rocking Movements on Respiration

For centuries, rocking has been used to promote sleep in babies or toddlers. Recent research suggested that relaxation could play a role in facilitating the transition from waking to sleep during rocking. Breathing techniques are often used to promote relaxation. However, studies investigating head motions and body rotations showed that vestibular stimulation might elicit a vestibulo-respiratory response, leading to an increase in respiration frequency. An increase in respiration frequency would not be considered to promote relaxation in the first place. On the other hand, a coordination of respiration to rhythmic vestibular stimulation has been observed. Therefore, this study aimed to investigate the effect of different movement frequencies and amplitudes on respiration frequency. Furthermore, we tested whether subjects adapt their respiration to movement frequencies below their spontaneous respiration frequency at rest, which could be beneficial for relaxation. Twenty-one healthy subjects (24–42 years, 12 males) were investigated using an actuated bed, moving along a lateral translation. Following movement frequencies were applied: +30%, +15%, -15%, and -30% of subjects’ rest respiration frequency during baseline (no movement). Furthermore, two different movement amplitudes were tested (Amplitudes: 15 cm, 7.5 cm; movement frequency: 0.3 Hz). In addition, five subjects (25–28 years, 2 males) were stimulated with their individual rest respiration frequency. Rocking movements along a lateral translation caused a vestibulo-respiratory adaptation leading to an increase in respiration frequency. The increase was independent of the applied movement frequencies or amplitudes but did not occur when stimulating with subjects’ rest respiration frequency. Furthermore, no synchronization of the respiration frequency to the movement frequency was observed. In particular, subjects did not lower their respiration frequency below their resting frequency. Hence, it was not feasible to influence respiration in a manner that might be considered beneficial for relaxation.

Evaluation of cardiac modulation in children in response to apnea/hypopnea using the Phone Oximeter(™)

Individuals with sleep disordered breathing (SDB) can experience changes in automatic cardiac regulation as a result of frequent sleep fragmentation and disturbance in normal respiration and oxygenation that accompany most apnea/hypopnea events. In adults, these changes are reflected in enhanced sympathetic and reduced parasympathetic activity. In this study, we examined the autonomic cardiac regulation in children with and without SDB, through spectral and detrended fluctuation analysis (DFA) of pulse rate variability (PRV). PRV was measured from pulse-to-pulse intervals (PPIs) of the photoplethysmogram (PPG) recorded from 160 children using the Phone Oximeter(™) in the standard setting of overnight polysomnography. Spectral analysis of PRV showed the cardiac parasympathetic index (high frequency, HF) was lower (p < 0.01) and cardiac sympathetic indices (low frequency, LF and LF/HF ratio) were higher (p < 0.01) during apnea/hypopnea events for more than 95% of children with SDB. DFA showed the short- and long-range fluctuations of heart rate were more strongly correlated in children with SDB compared to children without SDB. These findings confirm that the analysis of the PPG recorded using the Phone Oximeter(™) could be the basis for a new screening tool for assessing PRV in non-clinical environment.

Spectral analysis of heart rate variability

Spectral analysis (SA) has been extensively applied to the assessment of heart rate variability. Traditional methods require the transformation of the original non-uniformly spaced electrocardiogram RR interval series into regularly spaced ones using interpolation or other approaches. The Lomb-Scargle (L-S) method uses the raw original RR series, avoiding different artifacts introduced by traditional SA methods, but it has been scarcely used in clinical settings. An RR series was recorded from 120 healthy participants (17–25 years) of both genders during a resting condition using four SA methods, including the Classic modified periodogram, the Welch procedure, the autoregressive Burg method and the L-S method. The efficient implementation of the L-S algorithm with the added possibility of the application of a set of options for the RR series pre-processing developed by Eleuteri et al., and also the results obtained in this study, show that the L-S method can be a good choice for future clinical studies. The L-S method seems particularly useful when the heart rates of studied participants will be below 60 or over 120 beats per minute. Nevertheless, it is important to the development of a smoothing procedure for the L-S spectra to avoid the picky behavior of the L-S power spectrum. The implementation of the L-S algorithm used in this study has been recently published by other authors included in our references, and brings some particular filtering features. The results obtained, comparing the four spectral methods, show that this implementation seems particularly useful when the heart rates of studied participants will be below 60 or over 120 beats per minute. Nevertheless, it is important to recommend for all existing L-S software implementations, the development of a smoothing procedure to avoid the picky behavior of the L-S power spectrum.

Family stress moderates relations between physiological and behavioral synchrony and child self-regulation in mother-preschooler dyads

From a bio-behavioral framework, the relations between physiological synchrony, positive behavioral synchrony, and child self-regulation under varying levels of risk were examined among 93 mother- (M age = 30.44 years, SD = 5.98 years) preschooler (M age = 3.47 years, SD =.52 years, 58.70% male) dyads. Physiological synchrony was examined using interbeat interval (IBI) data and measures of positive behavioral synchrony and self-regulation were based on observations of a mother-child interaction task. Results supported the phenomenon of physiological synchrony among mother-preschooler dyads during an interaction, but not a baseline, task. Moderation analyses indicated that under conditions of high family risk, positive behavioral synchrony and child self-regulation were greater when physiological synchrony was low. Positive behavioral synchrony was positively associated with child self-regulation, regardless of risk status. The results document physiological synchrony among mothers and their preschool-aged children and the complex ways that physiological attunement relates to important developmental processes.

Affective Modulation of Brain and Autonomic Responses in Patients With Fibromyalgia

OBJECTIVES

Emotional dysregulation and abnormal processing of affective information are thought to play a significant role for the maintenance of pain in fibromyalgia. The motivational priming hypothesis states that negative emotions could increase pain via activation of the aversive system, thus leading to an affective modulation of defensive reflexes. Nevertheless, little is known about peripheral and central correlates of affective reflex modulation in fibromyalgia.

METHODS

Thirty patients with fibromyalgia and 30 healthy individuals were asked to view three video clips from a self-perspective to induce specific mood states. Video clips consisted of the same virtual walk through different locations of a park under three affective environments (unpleasant, pleasant, and neutral). Startle eyeblink reflex and heart rate response elicited by abrupt startle noises, as well as heart rate variability and electroencephalography (EEG) oscillations were recorded when participants were passively viewing the virtual environments.

RESULTS

Patients with fibromyalgia rated all environments as more negative and arousing than did healthy controls (p values < .05). Nevertheless, startle eyeblink reflex and heart rate response were lower in patients with fibromyalgia than in healthy controls when viewing all three environments (p values < .05). Patients with fibromyalgia also displayed lower heart rate variability, as well as higher EEG power (2-22 Hz) during all environments than did healthy controls (p values < .05).

CONCLUSIONS

Patients with fibromyalgia were characterized by relevant deficits in affective modulation of startle and cardiac responses, heart rate variability, and EEG power spectra in response to sustained induction of affective states. These findings suggest an alteration of emotional and attentional aspects of information processing at subjective, autonomic, and central nervous system levels.

Dynamic heart rate measurements from video sequences

This paper shows how dynamic heart rate measurements that are typically obtained from sensors mounted near to the heart can also be obtained from video sequences. In this study, two experiments are carried out where a video camera captures the facial images of the seven subjects. The first experiment involves the measurement of subjects' increasing heart rates (79 to 150 beats per minute (BPM)) while cycling whereas the second involves falling heart beats (153 to 88 BPM). In this study, independent component analysis (ICA) is combined with mutual information to ensure accuracy is not compromised in the use of short video duration. While both experiments are going on measures of heartbeat using the Polar heart rate monitor is also taken to compare with the findings of the proposed method. Overall experimental results show the proposed method can be used to measure dynamic heart rates where the root mean square error (RMSE) and the correlation coefficient are 1.88 BPM and 0.99 respectively.

Heightened vagal activity during high-calorie food presentation in obese compared with non-obese individuals--results of a pilot study

Eating behaviours are highly cue-dependent. Changes in mood states and exposure to palatable food both increase craving and consumption of food. Vagal activity supports adaptive modulation of physiological arousal and has an important role in cue-induced appetitive behaviours. Using high-frequency heart rate variability (HF HRV), this preliminary study compared vagal activity during positive and negative mood induction, and presentation of preferred high-calorie food items between obese (n = 12; BMI ≥ 30) and non-obese individuals (n = 14; 18.5 < BMI < 30). Participants completed two laboratory sessions (negative vs. positive mood conditions). Following 3-h of food deprivation, all participants completed a mood induction, and then were exposed to their preferred high-calorie food items. HF HRV was assessed throughout. Obese and non-obese individuals were not significantly different in HF HRV during positive or negative mood induction. Obese individuals showed significantly greater levels of HF HRV during presentation of their preferred high-calorie food items than non-obese individuals, particularly in the positive mood condition. This is the first study to demonstrate increased vagal activity in response to food cues in obese individuals compared with non-obese individuals. Our findings warrant further investigation on the potential role of vagally-mediated cue reactivity in overeating and obesity.

Heart rate variability and critical flicker fusion frequency changes during and after parachute jumping in experienced skydivers

PURPOSE

The purpose of this study was (1) to further explore the heart rate dynamics and assess a potential cardiovascular risk in response to 4000 m jumps in experienced skydivers; (2) to assess whether there is an impact of such jumps on skydivers' cortical arousal or not, which may impact their decision making processes.

METHOD

18 experienced skydivers performed successive jumps from a plane at 4000 m of height. Heart rate dynamics and cortical arousal were assessed by the use of heart rate variability and Critical Flicker Fusion Frequency (CFFF), respectively.

RESULTS

CFFF did not differ between the three measurement time points (p > 0.05). Mean heart rate increased during the jump (p < 0.001) and came back to pre-jump values after the jump (p < 0.001). Percentage of the differences of successive NN intervals greater than 50 ms (pNN50) decreased during the jump (p < 0.001) and kept lower values after the jump compared to pre-jump (p < 0.05). High-frequency power (HF) did not differ during the jump (p > 0.05) but decreased after the jump compared to both pre-jump (p < 0.01) and jump (p < 0.05). Sample entropy decreased during the jump (p < 0.001) and came back to pre-jump values after the jump (p > 0.05).

CONCLUSION

These results confirm a vagal input reduction associated with a rise of the sympathetic tone during the jump and suggests that the experienced skydiver is not exposed to a high cardiovascular risk. This study also shows that environmental stresses induced by free fall could not hamper the perceptual vigilance of experienced skydivers.