Combined heart rate variability and dynamic measures for quantitatively characterizing the cardiac stress status during cycling exercise

Assessment of mental workload based on multi-physiological signals

BACKGROUND:

Mental workload is one of the contributing factors to human errors in road accidents or other potentially adverse incidents.

OBJECTIVE:

This research probes the effects of mental workload on the electroencephalographic (EEG) and electrocardiogram (ECG) of subjects in visual monitoring tasks, based on which a comprehensive evaluation model for mental workload is established effectively.

METHODS:

Three degrees of mental workload were obtained by monitoring tasks with different levels of difficulty. 20 healthy subjects were selected to take part in the research.

RESULTS:

The subjective scores showed a significant increase with the increase of task difficulty, meanwhile the reaction time (RT) increased and the accuracy decreased significantly, which proved the validity of three degrees of mental workload induced. For the EEG parameters, a significant decrease of θ energy was found in Frontal, Parietal and Occipital with the increase of level of mental workload, as well as a significant decrease of α energy in Frontal, Central and Occipital, meanwhile a significant increase of β energy occurred in Frontal and Occipital. There was a significant decrease of α/θ in Occipital, and significant increases of θ/β and (α+β)/θ in Frontal, Central and Occipital, meanwhile (α+θ)/β and WPE decreased significantly in Frontal and Occipital. Among the ECG parameters, it was shown that Mean RR, RMSSD, HF_norm and SampEn decreased significantly with the increase of task difficulty, while LF_norm and LF/HF showed significant increases. These EEG indictors in Occipital and ECG indictors were chosen and constituted a multidimensional original sample. Principal Component Analysis (PCA) was used to extract the principal elements and decreased the dimension of sample space in order to simplify the calculation, based on which an effective classification model with accuracy of 80% was achieved by support vector machine (SVM).

CONCLUSION:

This study demonstrates that the proposed algorithm can be applied to mental workload monitoring.

Correlation properties of heart rate variability during endurance exercise: A systematic review

Background

Non‐linear measures of heart rate variability (HRV) may provide new opportunities to monitor cardiac autonomic regulation during exercise. In healthy individuals, the HRV signal is mainly composed of quasi‐periodic oscillations, but it also possesses random fluctuations and so‐called fractal structures. One widely applied approach to investigate fractal correlation properties of heart rate (HR) time series is the detrended fluctuation analysis (DFA). DFA is a non‐linear method to quantify the fractal scale and the degree of correlation of a time series. Regarding the HRV analysis, it should be noted that the short‐term scaling exponent alpha1 of DFA has been used not only to assess cardiovascular risk but also to assess prognosis and predict mortality in clinical settings. It has also been proven to be useful for application in exercise settings including higher exercise intensities, non‐stationary data segments, and relatively short recording times.

Method

Therefore, the purpose of this systematic review was to analyze studies that investigated the effects of acute dynamic endurance exercise on DFA‐alpha1 as a proxy of correlation properties in the HR time series.

Results

The initial search identified 442 articles (351 in PubMed, 91 in Scopus), of which 11 met all inclusion criteria.

Conclusions

The included studies show that DFA‐alpha1 of HRV is suitable for distinguishing between different organismic demands during endurance exercise and may prove helpful to monitor responses to different exercise intensities, movement frequencies, and exercise durations. Additionally, non‐linear DFA of HRV is a suitable analytical approach, providing a differentiated and qualitative view of exercise physiology.

Neonatal Skin-to-Skin Contact: Implications for Learning and Autonomic Nervous System Function in Infants With Congenital Heart Disease

Background:

Infants with complex congenital heart disease (CCHD) often develop neurodevelopmental disabilities. Cognitive abilities are associated with vagally mediated autonomic function. Skin-to-skin contact (SSC) interventions enhance infant neurodevelopment and autonomic function in other high-risk populations.

Aim:

To examine the effects of a neonatal SSC intervention on learning and autonomic function in 3-month-old infants: infants with CCHD who received neonatal SSC ( n = 10), typically developing (TD) infants ( n = 16), and infants with CCHD without SSC ( n = 10).

Methods:

This secondary data analysis measured cognitive function using the mobile paradigm (MP), a classic measure of learning based on operant conditioning. Autonomic function was assessed with heart rate (HR) and HR variability (HRV). Data were analyzed with repeated-measures general linear mixed modeling with α = .10 for this exploratory study.

Results:

Learning rates were TD = 75%, cardiac-SSC = 70%, and cardiac-control = 40%. Learners demonstrated significant reductions in HRV during the MP; nonlearners exhibited no change. TD and cardiac-SSC groups exhibited increases in HR and reductions in HRV during the MP. No significant changes occurred in the cardiac-control group. Nonlinear HRV during the MP differed only in the TD group.

Conclusions:

Findings suggest improvements in cognitive and autonomic development in 3-month-old infants with CCHD who received neonatal SSC. Learning and autonomic function results in infants with CCHD who had not received SSC suggest reduced capacity to muster the physiologic resources to carry out this cognitive task. Findings provide preliminary evidence in support of implementation of SSC with infants with CCHD and support additional research.

Influence of visual elicitation over emotion regulation: An investigation employing the heart rate variability

Several works studied the elicitation of emotions through the exposure of individuals to relevant stimuli, using spectral analysis of Heart Rate Variability (HRV) when people are subject to emotional elicitation. If correlation exists between HRV and emotional responses, spectral analysis can be used to study emotion regulation under external stimuli. In this work, we studied the relationship between visual elicitation and emotion regulation, employing HRV. Images (with pleasant, unpleasant and neutral emotional content) were selected from the IAPS (International Affective Picture System) dataset. Ninety-eight participants were enrolled, and subject to view all images, displayed in random order for each participant. Heart rate was recorded during the experiment, and HRV analysis was performed. Spectral values were studied for the different images. The presentation order of images was relevant, mainly when unpleasant images were viewed in first place; this significantly affects HRV values. Spectral values were higher for men, being this difference stronger when pleasant pictures were displayed. Age and gender dependences of spectral indexes were found. The influence of visual elicitation, with different emotional contents, over HRV, was assessed. Results indicate that HRV parameters are affected when individuals are subject to external, emotional-based stimuli.

gVARVI: A graphical software tool for the acquisition of the heart rate in response to external stimuli

BACKGROUND AND OBJECTIVE

At present, tools capable of acquiring heart rate data can be found both in commercial and research fields. However, these tools do not allow users to manage experiments comprising sequences of activities or to store the information needed to perform heart rate variability analysis across different activities. One exception is VARVI, a simple software tool developed previously in our research group that does not have a graphical user interface and it works only with visual stimuli. In this paper, we present gVARVI, a software tool aimed at obtaining heart rate data signals while the user is either receiving a sequence of external stimuli or performing a sequence of actions (an activity).

METHODS

gVARVI is an open source application developed in Python programming language. It can acquire heart rate data by means of a wireless chest strap using either Bluetooth or ANT+ protocols. Users can define activities of different types (video, sounds, pictures or keyboard controlled actions) which will associate contextual information to the heart rate data. gVARVI allows users to preview this data or to store it to be used for heart rate variability studies. Our tool was validated by 15 researchers, who worked with the application and filled in a usability questionnaire.

RESULTS

The outcome of the usability test was satisfactory, giving a mean score of 4.75 in a 1-5 scale (1 - strongly disagree, 5 - strongly agree). Participants also contributed with valuable comments, which we used to include new features in the last version of our tool.

CONCLUSIONS

gVARVI is an open source tool that offers new possibilities to both physicians and clinicians to perform heart rate variability studies. It allows users to acquire heart rate data including information on the activity performed by subjects while recording. In this paper, we describe all the functionalities included in gVARVI, and a complete example of use is provided.

Beneficial Effect of Preferential Music on Exercise Induced Changes in Heart Rate Variability

INTRODUCTION

Music is known to reduce pain, anxiety and fear in several stressful conditions in both males and females. Further, listening to preferred music enhances the endurance during running performance of women rather than listening to non-preferred music. In recent years Heart Rate Variability (HRV) has been used as an indicator of autonomic nervous activity.

AIM

This study was aimed to assess the effectiveness of preferential music on HRV after moderate exercise.

MATERIALS AND METHODS

This was an experimental study done in 30 healthy students aged between 20-25 years, of either sex. HRV was measured at rest, 15 minutes of exercise only and 15 minutes of exercise with listening preferential music in same participants. Data was analysed by One-Way ANOVA and Tukey HSD Post-hoc Test. Statistical significance was taken to be a p-value of less than 0.05.

RESULTS

Low frequency and high frequency component was significantly increased followed by only exercise. Music minimized increase in both high and low frequency component followed by exercise. However, only high frequency change was statistically significant. LF/HF ratio was significantly increased followed by only exercise. Music significantly minimized increase in LF/HF ratio.

CONCLUSION

This study provides the preliminary evidence that listening to preferential music could be an effective method of relaxation, as indicated by a shift of the autonomic balance towards the parasympathetic activity among medical students.