Heart rate variability behavior in young men after short-term carotenoid-containing supplementation

Background

Heart rate variability can reflect the risk of developing cardiovascular disease (CVD), while carotenoids are good for CVD prevention. However, the acute effect of short-term carotenoid-containing supplementation on heart rate variability in young men is unclear.

Methods

Thirty young men between 20 and 29 years of age without personal or family history of cardiovascular diseases were randomly divided into control and experimental groups. The anthropometric data, physiological parameters, and serum biochemical data were acquired, which were without significant difference between the two groups, at the beginning of trial. The participants in the experimental group consumed one pack of compound nutritional supplements in the morning (e.g., 10 AM) and another pack at night (e.g., 7 PM) each day. Heart rate variability was measured again once a month. Repeated measures analysis of variance with Roy's largest root test and Bonferroni post hoc test were applied for primary outcomes.

Results

Repeated measures analysis of variance indicated a significant time interaction effect for the estimated marginal means of percussion entropy index scale (T1 versus T3, T1 versus T4, and T2 versus T4 with p = 0.009, 0.005, and 0.032, respectively). Roy's largest root test indicates there were significant differences between the means of the index after the intervention between two groups only on T3 and T4 (p = 0.007, η ² = 0.232 and p = 0.028, η ² = 0.162, respectively).

Conclusion

Short-term carotenoid-containing supplementation could help young men by increasing heart rate variability capacity compared to controls over three months.

Stress of emergency physicians during helicopter operations: impact of patients' diagnoses, severity of diagnoses, and physicians' work experience

PURPOSE

Emergency physicians are in danger of developing illnesses due to stress in their demanding work environment. Until today, scholars have not identified stressors or resilience factors that qualify to promote the preservation of emergency physicians' well-being. Therefore, potential influencing variables such as patients' diagnoses, the severity of diagnoses, as well as physicians' work experience have to be considered. The present study aims at investigating emergency physicians in the Helicopter Emergency Medical Service (HEMS)' autonomic nervous system activity during emergency operations in one shift with respect to patients' diagnoses, severity of diagnoses, and physicians' work experience.

METHODS

Measurement of HRV (employing the parameters RMSSD and LF/HF) for 59 EPs (age: M = 39.69, SD = 6.19) was performed during two complete air-rescue-days, the alarm and landing phase being investigated in particular. Besides patients' diagnoses, the National Advisory Committee for Aeronautics Score (NACA) was included as an indicator for severity. Diagnoses' and NACA's effect on HRV were examined using a linear mixed model.

RESULTS

Both HRV parameters indicate a significant decrease of the parasympathetic nervous system as a function of the diagnoses. Furthermore, high NACA scores (≥ V) predicted a significantly lower HRV. In addition, a lower HRV/RMSSD with increasing work experience was observed as well as a positive association between physicians' work experience and sympathetic activation (LF/HF).

CONCLUSION

The present study showed that pediatric diagnoses as well as time-critical diagnoses are most stressful and have the highest impact on the physicians' ANS. This knowledge allows the development of specific training to reduce stress.

Using Heart Rate Variability Methods for Health-Related Outcomes in Outdoor Contexts: A Scoping Review of Empirical Studies

Heart rate variability (HRV) is a psychophysiological variable that is often used in applied analysis techniques to indicate health status because it provides a window into the intrinsic regulation of the autonomic nervous system. However, HRV data analysis methods are varied and complex, which has led to different approaches to data collection, analysis, and interpretation of results. Our scoping review aimed to explore the diverse use of HRV methods in studies designed to assess health outcomes in outdoor free-living contexts. Four database indexes were searched, which resulted in the identification of 17,505 candidate studies. There were 34 studies and eight systematic reviews that met the inclusion criteria. Just over half of the papers referenced the 1996 task force paper that outlined the standards of measurement and physiological interpretation of HRV data, with even fewer adhering to recommended HRV recording and analysis procedures. Most authors reported an increase in parasympathetic (n = 23) and a decrease in systematic nervous system activity (n = 20). Few studies mentioned methods-related limitations and challenges, despite a wide diversity of recording devices and analysis software used. We conclude our review with five recommendations for future research using HRV methods in outdoor and health-related contexts.

Decoding the correlation between heart activation and walking path by information-based analysis

BACKGROND

One of the important areas of heart research is to analyze heart rate variability during (HRV) walking.

OBJECTIVE

In this research, we investigated the correction between heart activation and the variations of walking paths.

METHOD

We employed Shannon entropy to analyze how the information content of walking paths affects the information content of HRV. Eight healthy students walked on three designed walking paths with different information contents while we recorded their ECG signals. We computed and analyzed the Shannon entropy of the R-R interval time series (as an indicator of HRV) versus the Shannon entropy of different walking paths and accordingly evaluated their relation.

RESULTS

According to the obtained results, walking on the path that contains more information leads to less information in the R-R time series.

CONCLUSION

The analysis method employed in this research can be extended to analyze the relation between other physiological signals (such as brain or muscle reactions) and the walking path.

Feasibility of Ultra-Short-Term Analysis of Heart Rate and Systolic Arterial Pressure Variability at Rest and during Stress via Time-Domain and Entropy-Based Measures

Heart Rate Variability (HRV) and Blood Pressure Variability (BPV) are widely employed tools for characterizing the complex behavior of cardiovascular dynamics. Usually, HRV and BPV analyses are carried out through short-term (ST) measurements, which exploit ~five-minute-long recordings. Recent research efforts are focused on reducing the time series length, assessing whether and to what extent Ultra-Short-Term (UST) analysis is capable of extracting information about cardiovascular variability from very short recordings. In this work, we compare ST and UST measures computed on electrocardiographic R-R intervals and systolic arterial pressure time series obtained at rest and during both postural and mental stress. Standard time-domain indices are computed, together with entropy-based measures able to assess the regularity and complexity of cardiovascular dynamics, on time series lasting down to 60 samples, employing either a faster linear parametric estimator or a more reliable but time-consuming model-free method based on nearest neighbor estimates. Our results are evidence that shorter time series down to 120 samples still exhibit an acceptable agreement with the ST reference and can also be exploited to discriminate between stress and rest. Moreover, despite neglecting nonlinearities inherent to short-term cardiovascular dynamics, the faster linear estimator is still capable of detecting differences among the conditions, thus resulting in its suitability to be implemented on wearable devices.

Beneficial Effects of Black Cardamom (Amomum subulatum) on Hemodynamic Parameters in Normotensive and Spontaneously Hypertensive Rats

<b>Background and Objectives:</b> <i>Amomum subulatum</i> (AS) is used to improve cardiac health in traditional medicine practice. The present study evaluates the pharmacological effect of AS aqueous extract on blood pressure in Normotensive (NR) and Spontaneously Hypertensive Rats (SHR). <b>Materials and Methods:</b> Blood pressure, Heart Rate (HR) and Heart Rate Variability (HRV), was recorded in catheterized Sprague-Dawley rats before and after AS intravenous administration by using Mikro-Tip Pressure-Volume System (MPVS), PowerLab. The receptor activity was assessed by using the drugs Acetylcholine (ACh) and Atropine (Atr). <b>Results:</b> Preliminary phytochemistry of AS suggests that it contains tannins, flavonoids and saponins. Mean Arterial Pressure (MAP) was found to decrease significantly in NR and SHR as compared with the control. The lowest dose (1 mg kg<sup></sup><sup>1</sup>) produced the least (16%) while 30 mg kg<sup></sup><sup>1</sup> caused the maximum reduction (40%) in MAP. Electrocardiograph analysis revealed a significant increase in RR interval (decreased heart rate), time-domain Standard Deviation of Interbeat Interval (SDNN) and the Root Mean Square of the Successive Differences (RMSSD) and High-frequency Domain (HF%) parameters and a decrease in the Low-Frequency (LF) range, suggesting the activation and involvement of the parasympathetic limb. It was also observed that the cardiovascular effects of AS were comparable to Acetylcholine (ACh) and both were completely blocked by Atropine (1 μg kg<sup></sup><sup>1</sup>). <b>Conclusion:</b> The obtained results suggest that AS has a hypotensive effect, with an impact on the HRV of NR and SHR. <i>Amomum subulatum</i> might cause an augmented effect on the cholinergic limb of the Autonomic Nervous System (ANS) and decrease the blood pressure and heart rate significantly.

Influence of Different Types of Corticosteroids on Heart Rate Variability of Individuals with Duchenne Muscular Dystrophy-A Pilot Cross Sectional Study

Individuals with Duchenne Muscular Dystrophy (DMD) have an impairment of cardiac autonomic function categorized by parasympathetic reduction and sympathetic predominance. The objective of this study was to assess the cardiac autonomic modulation of individuals with DMD undergoing therapy with Prednisone/Prednisolone and Deflazacort and compare with individuals with DMD without the use of these medications and a typically developed control group. Methods: A cross-sectional study was completed, wherein 40 boys were evaluated. The four treatment groups were: Deflazacort; Prednisone/Prednisolone; no corticoid use; and typical development. Heart Rate Variability (HRV) was investigated via linear indices (Time Domain and Frequency Domain) and non-linear indices Results: The results of this study revealed that individuals with DMD undertaking pharmacotherapies with Prednisolone demonstrated HRV comparable to the Control Typically Developed (CTD) group. In contrast, individuals with DMD undergoing pharmacotherapies with Deflazacort achieved lower HRV, akin to individuals with DMD without any medications, as demonstrated in the metrics: RMSSD; LF (n.u.), HF (n.u.), LF/HF; SD1, α1, and α1/α2, and a significant effect for SD1/SD2; %DET and Ratio; Shannon Entropy, 0 V%, 2 LV% and 2 ULV%. Conclusions: Corticosteroids have the potential to affect the cardiac autonomic modulation in adolescents with DMD. The use of Prednisone/Prednisolone appears to promote improved responses in terms of sympathovagal activity as opposed to Deflazacort.

Heart Rate Variability measured during rest and after orthostatic challenge to detect autonomic dysfunction in Type 2 Diabetes Mellitus using the Classification and Regression Tree model

BACKGROUND

According to the World Health Organization, one in ten adults will have Type 2 Diabetes Mellitus (T2DM) in the next few years. Autonomic dysfunction is one of the significant complications of T2DM. Autonomic dysfunction is usually assessed by standard Ewing's test and resting Heart Rate Variability (HRV) indices.

OBJECTIVE

Resting HRV has limited use in screening due to its large intra and inter-individual variations. Therefore, a combined approach of resting and orthostatic challenge HRV measurement with a machine learning technique was used in the present study.

METHODS

A total of 213 subjects of both genders between 20 to 70 years of age participated in this study from March 2018 to December 2019 at Smt. Kashibai Navale Medical College and General Hospital (SKNMCGH) in Pune, India. The volunteers were categorized according to their glycemic status as control (n= 51 Euglycemic) and T2DM (n= 162). The short-term ECG signal in the resting and after an orthostatic challenge was recorded. The HRV indices were extracted from the ECG signal as per HRV-Taskforce guidelines.

RESULTS

We observed a significant difference in time, frequency, and non-linear resting HRV indices between the control and T2DM groups. A blunted autonomic response to an orthostatic challenge quantified by percentage difference was observed in T2DM compared to the control group. HRV patterns during rest and the orthostatic challenge were extracted by various machine learning algorithms. The classification and regression tree (CART) model has shown better performance among all the machine learning algorithms. It has shown an accuracy of 84.04%, the sensitivity of 89.51%, a specificity of 66.67%, with an Area Under Receiver Operating Characteristic Curve (AUC) of 0.78 compared to resting HRV alone with 75.12% accuracy, 86.42% sensitivity, 39.22% specificity, with an AUC of 0.63 for differentiating autonomic dysfunction in non-diabetic control and T2DM.

CONCLUSION

It was possible to develop a Classification and Regression Tree (CART) model to detect autonomic dysfunction. The technique of percentage difference between resting and orthostatic challenge HRV indicates the blunted autonomic response. The developed CART model can differentiate the autonomic dysfunction using both resting and orthostatic challenge HRV data compared to only resting HRV data in T2DM. Thus, monitoring HRV parameters using the CART model during rest and after orthostatic challenge may be a better alternative to detect autonomic dysfunction in T2DM as against only resting HRV.

The Association between Self-Reported Difficulties in Emotion Regulation and Heart Rate Variability: The Salient Role of Not Accepting Negative Emotions

Difficulties in emotion regulation are associated with development and maintenance of psychopathology. Typically, features of emotion regulation are assessed with self-report questionnaires. Heart rate variability (HRV) is an objective measure proposed as an index of emotional regulation capacity. A limited number of studies have shown that self-reported difficulties in emotion regulation are associated with HRV. However, results from prior studies are inconclusive, and an ecological validation of the association has not yet been tested. Therefore, further exploration of the relation between self-report questionnaires and psychophysiological measures of emotional regulation is needed. The present study investigated the contribution of self-reported emotion regulation difficulties on HRV in a student sample. We expected higher scores on emotion regulation difficulties to be associated with lower vagus-mediated HRV (vmHRV). Sixty-three participants filled out the Difficulties in Emotion Regulation Scale and their resting HRV was assessed. In addition, a subsample of participants provided ambulatory 24-h HRV data, in order to ecologically validate the resting data. Correlation analyses indicated that self-reported difficulties in emotion regulation was negatively associated with vmHRV in both resting HRV and 24-h HRV. Specifically, when exploring the contribution of the different facets of emotion dysregulation, the inability to accept negative emotions showed the strongest association with HRV. The results are discussed and need for future research is described.

Monitoring of autonomic response to sociocognitive tasks during treatment in children with Autism Spectrum Disorders by wearable technologies: A feasibility study

BACKGROUND

Autism Spectrum Disorders (ASD) represent a heterogeneous set of neurodevelopmental disorders characterized by impairments in social domain, where the autonomic nervous system (ANS) plays an important role. Several researchers have studied the ANS in ASD, during specific cognitive or sensory stimuli while few studies have examined response during social interactions. Wearable technologies can be very helpful in monitoring autonomic response in children with ASD in semi-naturalistic setting. The novelty of this study is to use such technologies to acquire physiological signals during therapeutic sessions supported by interactive "serious games" and to correlate the ANS response to the engagement of the child during sociocognitive tasks for an evaluation of the treatment effect and for the personalization of the therapy.

METHOD

A wearable chest belt for electrocardiographic (ECG) signal recording was used and specific algorithms for the extraction of clinically relevant features (Heart Rate - HR, Root Mean Square of the Successive Differences - RMSSD and Respiratory Sinus Arrhythmia - RSA) were developed. Sociocognitive tasks were mediated by "serious games" implemented on two tablets, which allowed a precise coding of the behaviors of the children. A longitudinal assessment of the physiological response of the children during six months of treatment was performed.

RESULTS

A link between physiological response, i.e. decrease in RMSSD and RSA, and engagement of the children during sociocognitive tasks was found. Longitudinal changes in the children's autonomic response, including a decrease of RSA during the engagement throughout the therapeutic sessions, were found.

CONCLUSIONS

These results foster the feasibility of this methodology to be applied in a clinical setting for the monitoring of the ANS response of children with ASD during treatment. A larger sample of patients is needed to confirm these preliminary findings.

Investigation of the relationship between anxiety and heart rate variability in fibromyalgia: A new quantitative approach to evaluate anxiety level in fibromyalgia syndrome

BACKGROUND

Fibromyalgia syndrome (FMS) is identified by widespread musculoskeletal pain, sleep disturbance, nonrestorative sleep, fatigue, morning stiffness and anxiety. Anxiety is very common in Fibromyalgia and generally leads to a misdiagnosis. Self-rated Beck Anxiety Inventory (BAI) and doctor-rated Hamilton Anxiety Inventory (HAM-A) are frequently used by specialists to determine anxiety that accompanies fibromyalgia. However, these semi-quantitative anxiety tests are still subjective as the tests are scored using doctor-rated or self-rated scales.

METHOD

In this study, we investigated the relationship between heart rate variability (HRV) frequency subbands and anxiety tests. The study was conducted with 56 FMS patients and 34 healthy controls. BAI and HAM-A test scores were determined for each participant. ECG signals were then recruited and 71 HRV subbands were obtained from these ECG signals using Wavelet Packet Transform (WPT). The subbands and anxiety tests scores were analyzed and compared using multilayer perceptron neural networks (MLPNN).

RESULTS

The results show that a HRV high frequency (HF) subband in the range of 0.15235Hz to 0.40235Hz, is correlated with BAI scores and another HRV HF subband, frequency range of 0.15235Hz to 0.28907Hz is correlated with HAM-A scores. The overall accuracy is 91.11% for HAM-A and 90% for BAI with MLPNN analysis.

CONCLUSION

Doctor-rated or self-rated anxiety tests should be supported with quantitative and more objective methods. Our results show that the HRV parameters will be able to support the anxiety tests in the clinical evaluation of fibromyalgia. In other words, HRV parameters can potentially be used as an auxiliary diagnostic method in conjunction with anxiety tests.

An Efficient Biometric-Based Algorithm Using Heart Rate Variability for Securing Body Sensor Networks

Body Sensor Network (BSN) is a network of several associated sensor nodes on, inside or around the human body to monitor vital signals, such as, Electroencephalogram (EEG), Photoplethysmography (PPG), Electrocardiogram (ECG), etc. Each sensor node in BSN delivers major information; therefore, it is very significant to provide data confidentiality and security. All existing approaches to secure BSN are based on complex cryptographic key generation procedures, which not only demands high resource utilization and computation time, but also consumes large amount of energy, power and memory during data transmission. However, it is indispensable to put forward energy efficient and computationally less complex authentication technique for BSN. In this paper, a novel biometric-based algorithm is proposed, which utilizes Heart Rate Variability (HRV) for simple key generation process to secure BSN. Our proposed algorithm is compared with three data authentication techniques, namely Physiological Signal based Key Agreement (PSKA), Data Encryption Standard (DES) and Rivest Shamir Adleman (RSA). Simulation is performed in Matlab and results suggest that proposed algorithm is quite efficient in terms of transmission time utilization, average remaining energy and total power consumption.