An approach to remote monitoring of heart rate variability (HRV) using microwave radar during a calculation task

Recently, nonrestrictive and noninvasive sensing techniques to measure vital signs have been actively researched and developed. This study aimed to develop a prototype system to monitor cardiac activity using microwave radar without making contact with the body and without removing clothing--namely, a completely noncontact, remote monitoring system. In addition, heart rate and changes in heart rate variability (HRV) during simple mental arithmetic tasks were observed with the prototype system. The prototype system has a microwave Doppler radar antenna with 24 GHz frequency and approximately 7 mW output power. The experiments were conducted with seven subjects (23.00±0.82 years). We found that the prototype system captured heart rate and HRV precisely. The strong relationship between the heart rates during tasks (r=0.96), LF (cross-correlation=0.76), and LF/HF (cross-correlation=0.73) of HRV calculated from the prototype system and from electrocardiograph (ECG) measurements were confirmed. The proposed completely noncontact, remote method appears promising for future monitoring of cardiac activity as an indicator of changes in mental workload in workplaces.     

Heart Rate Variability as a Marker of Self-Regulation

Self-regulation is central to many of the most important individual and societal problems today. We sought to determine whether the relationship between self-regulation and heart rate variability (HRV) could be replicated and extended. We hypothesized that baseline HRV would predict persistence on an anagram task, and that under conditions requiring greater self-control, HRV would increase. Two groups were given the same set of difficult and unsolvable anagrams. To induce self-regulatory fatigue, the suppression group was asked to try to not think of a white bear while the expression group was asked to try to think of a white bear. Baseline HRV predicted persistence on the unsolvable anagram. Both groups demonstrated changes in HRV relative to baseline, although we were unable to replicate findings that HRV was elevated during high self-regulatory effort. We were, however, able to replicate findings that the expression group persisted longer on the anagram task compared to the suppression group but only when accounting for physical activity scores. The present study advances our knowledge of the relationship between HRV and self-regulation, so that we can more successfully treat those with seriously impaired self-control.     

Cardiovascular reactivity to mental stress: relationship with menstrual cycle and gender

The purpose of the present study was to determine the fluctuation in cardiovascular reactivity to mental stress during the menstrual cycle by comparing heart rate variability (HRV), and other physiological and psychological data in females with those in males. Cardiovascular reactivity to two mental tasks was measured in 14 females during the follicular and luteal phase of menstruation over two menstrual cycles. The same tasks were subsequently given to a matched pair of males (N=14), at the same intervals as their corresponding females. Heart rate, blood pressure and HRV were used as indices of cardiovascular reactivity. Subjective mental workload was measured at the end of each task. Power spectral analysis of HRV showed that the high frequency (HF) component in HRV decreased more during the luteal phase than the follicular phase. The low frequency (LF) component in HRV and the LF/HF ratio in the luteal phase were significantly higher than that in the follicular phase. The LF component and the LF/HF ratio were significantly lower in females than in males; conversely, the HF component was significantly higher in females than in males. Neither significant effects of menstrual cycle, gender and mental stress nor any significant interactions were found for mental workload. These findings indicate that sympathetic nervous activity in the luteal phase is significantly greater than in the follicular phase whereas parasympathetic nervous activity is predominant in the follicular phase. The results also suggest that predominance of sympathetic nervous activity in males compared with a dominant parasympathetic nervous activity in females.     

Development of a Quantitative Real-Time Nucleic Acid Sequence-Based Amplification Assay with an Internal Control Using Molecular Beacon Probes for Selective and Sensitive Detection of Human Rhinovirus Serotypes

Evidence demonstrating that human rhinovirus (HRV) disease is not exclusively limited to the upper airways and may cause lower respiratory complications, together with the frequency of HRV infections and the increasing number of immunocompromised patients underline the need for rapid and accurate diagnosis of HRV infections. In this study, we developed the first quantitative real-time nucleic acid sequence-based amplification assay with an internal control using molecular beacon probes for selective and sensitive detection of human rhinovirus serotypes. We described a simple method to accurately quantify RNA target by computing the time to positivity (TTP) values for HRV RNA. Quantification capacity was assessed by plotting these TTP values against the starting number of target molecules. By using this simple method, we have significantly increased the diagnostic accuracy, precision, and trueness of real-time NASBA assay. Specificity of the method was verified in both in silico and experimental studies. Moreover, for assessment of clinical reactivity of the assay, NASBA has been validated on bronchoalveolar lavage (BAL) specimens. Our quantitative NASBA assay was found to be very specific, accurate, and precise with high repeatability and reproducibility.     

Simulating multi-agent-based computation offloading for autonomous cars

Efficient task processing and data storage are still among the most important challenges in Autonomous Driving (AD). In-board processing units struggle to deal with the workload of AD tasks, especially for Artificial Intelligence (AI) based applications. Cloud and Fog computing represent good opportunities to overcome the limitation of in-board processing capacities. However, communication delays and task real-time constraints are the main issues to be considered during the task mapping. Also, a fair resources allocation is a miss-explored concept in the context of AD task offloading where the mobility increases its complexity. We propose a task offloading simulation tool and approaches based on intelligent agents. Agents at the edge and the fog communicate and exchange their knowledge and history. We show results and proof-of-concept scenarios that illustrate our multi-agent-based proposition and task offloading simulation tool. We also analyze the impact of communication delays and processing units constraints on AD task offloading issues.

     

The variability of the heart rhythm and the nature of the feedback as a result of operator activity in man]

In a memory task which required sustained attention, the positive or negative emotional state of an operator was created by introduction of two different types of feedback in accordance with the number of correct or wrong solutions. Standard and original indices were used for evaluation of the short-term variability of the heart rate (HRV) during performance. Changes in the HRV were observed only in the periods of performance with the failure type of the feedback. These changes reflected stabilization of heart bit-to-bit intervals. The original index of the fast HRV turned to be the most sensitive for testing HRV changes. Human autonomic reactions of such a kind during operator-like activity are known as a predictor for the functional state of dissatisfaction. This confirms the practical importance of application of the HRV indices for testing the ergonomic properties of the systems which control the operator-computer interaction.     

Comparing the HRV Time-Series Signals Acquired from Cannabis Consuming and Non-Consuming Indian Paddy-Field Workers by Recurrence Quantification Analysis

ObjectiveIn the last few decades, the consumption of cannabis-based products for recreational purposes has dramatically increased. Unfortunately, cannabis consumption has been associated with the incidences of cardiovascular diseases. Hence, there is a necessity for understanding the plausible mechanics of cardiophysiological changes due to cannabis consumption. Accordingly, the current study was designed to understand the suitability of the recurrence quantification analysis (RQA) method in detecting the changes in the heart rate variability (HRV) time-series signals due to the consumption of cannabis (bhang). Further, a machine learning model has been proposed for the automated detection of the cannabis takers.Materials and MethodsThe RQA of the HRV time-series signals from 200 healthy Indian male paddy-field workers were carried out. The obtained parameters were statistically analyzed using the Mann-Whitney U test. Further, the decision trees, weight-based feature ranking, and dimensionality reduction methods were employed for identifying the relevant features for the development of a suitable machine learning model.ResultsObservable changes in the patterns of the recurrence plots among the bhang consuming and non-consuming groups were noticed. However, there were no significant differences in the RQA parameters. Among the developed machine learning models, the SVM model obtained from the “Information gain ratio” feature selection method exhibited the highest accuracy (%) of 69.09 ± 9.33.ConclusionOur study suggests that the RQA method is not as effective as the time and frequency domain methods for detecting the alterations in the HRV time-series signals due to cannabis consumption. The SVM model was found to be the best model for the automated detection of cannabis takers. The selection of the features by the information gain ratio method played an important role in the development of the optimized SVM model.     

Preliminary Results of an Open Label Study of Heart Rate Variability Biofeedback for the Treatment of Major Depression

Major depressive disorder (MDD) is a common mood disorder that can result in significant discomfort as well as interpersonal and functional disability. A growing body of research indicates that autonomic function is altered in depression, as evidenced by impaired baroreflex sensitivity, changes in heart rate, and reduced heart rate variability (HRV). Decreased vagal activity and increased sympathetic arousal have been proposed as major contributors to the increased risk of cardiovascular mortality in participants with MDD, and baroreflex gain is decreased. STUDY OBJECTIVES: To assess the feasibility of using HRV biofeedback to treat major depression. DESIGN: This was an open-label study in which all eleven participants received the treatment condition. Participants attended 10 weekly sessions. Questionnaires and physiological data were collected in an orientation (baseline) session and Treatment Sessions 1, 4, 7 and 10. MEASUREMENTS AND RESULTS: Significant improvements were noted in the Hamilton Depression Scale (HAM-D) and the Beck Depression Inventory (BDI-II) by Session 4, with concurrent increases in SDNN, standard deviation of normal cardiac interbeat intervals) an electrocardiographic estimate of overall measure of adaptability. SDNN decreased to baseline levels at the end of treatment and at follow-up, but clinically and statistically significant improvement in depression persisted. Main effects for task and session occurred for low frequency range (LF) and SDNN. Increases in these variables also occurred during breathing at one's resonant frequency, which targets baroreflex function and vagus nerve activity, showing that subjects performed the task correctly. CONCLUSIONS: HRV biofeedback appears to be a useful adjunctive treatment for the treatment of MDD, associated with large acute increases in HRV and some chronic increases, suggesting increased cardiovagal activity. It is possible that regular exercise of homeostatic reflexes helps depression even when changes in baseline HRV are smaller. A randomized controlled trial is warranted.     

Performance assessment of new-generation Fitbit technology in deriving sleep parameters and stages

ABSTRACT

We compared performance in deriving sleep variables by both Fitbit Charge 2?, which couples body movement (accelerometry) and heart rate variability (HRV) in combination with its proprietary interpretative algorithm (IA), and standard actigraphy (Motionlogger® Micro Watch Actigraph: MMWA), which relies solely on accelerometry in combination with its best performing ‘Sadeh’ IA, to electroencephalography (EEG: Zmachine® Insight+ and its proprietary IA) used as reference. We conducted home sleep studies on 35 healthy adults, 33 of whom provided complete datasets of the three simultaneously assessed technologies. Relative to the Zmachine EEG method, Fitbit showed an overall Kappa agreement of 54% in distinguishing wake/sleep epochs and sensitivity of 95% and specificity of 57% in detecting sleep epochs. Fitbit, relative to EEG, underestimated sleep onset latency (SOL) by ~11 min and overestimated sleep efficiency (SE) by ~4%. There was no statistically significant difference between Fitbit and EEG methods in measuring wake after sleep onset (WASO) and total sleep time (TST). Fitbit showed substantial agreement with EEG in detecting rapid eye movement and deep sleep, but only moderate agreement in detecting light sleep. The MMWA method showed 51% overall Kappa agreement with the EEG one in detecting wake/sleep epochs, with sensitivity of 94% and specificity of 53% in detecting sleep epochs. MMWA, relative to EEG, underestimated SOL by ~10 min. There was no significant difference between Fitbit and MMWA methods in amount of bias in estimating SOL, WASO, TST, and SE; however, the minimum detectable change (MDC) per sleep variable with Fitbit was better (smaller) than with MMWA, respectively, by ~10 min, ~16 min, ~22 min, and ~8%. Overall, performance of Fitbit accelerometry and HRV technology in conjunction with its proprietary IA to detect sleep vs. wake episodes is slightly better than wrist actigraphy that relies solely on accelerometry and best performing Sadeh IA. Moreover, the smaller MDC of Fitbit technology in deriving sleep parameters in comparison to wrist actigraphy makes it a suitable option for assessing changes in sleep quality over time, longitudinally, and/or in response to interventions.     

聚丙烯酰胺凝胶碎块吸收洗脱法浓缩病毒的实验研究及应用

本文报告聚丙烯酰胺凝胶(PAG)碎块吸收洗脱法在浓缩新城鸡瘟病毒(NDV)和人轮状病毒(HRV)方面的实验研究及应用。我们通过一次和二次浓缩,分别将NDV感染的鸡胚尿液稀释液浓缩了12.1倍和90.2倍,血凝滴度相应增高,总病毒回收率分别达到90.2％84.9％。用二次浓缩后的含HRV粪便上清液进行RNA PAGE银染色检测,获得了HRV RNA电泳型检测阳性稀释度提高32倍左右的结果。据此,采用这一方法,对临床RNA PAGE检测阴性的33例婴幼儿腹泻粪便进行PAG浓缩处理后再检测,发现有12例转为阳性,阳转率为36.4％。从而,使HRV总检出率由67％增至79％。     

Evaluation of mental task strain based on occipital beta activity and subjective rating of task difficulty

Occipital midline beta-2 (Oz beta 2) amplitudes and subjective ratings of task difficulty were measured in 24 healthy male students, aged 19-23 years, performing four kinds of mental task (transcribing, cancelling, adding, and calculating) at two grades of self-pace (maximum workload and moderate workload) for 5 min each. Significant differences in Oz beta 2 amplitudes were observed between the tasks at either workload, except between the adding task and the calculating task. However no significant difference in the subjective ratings was observed between the tasks at either workload, except between the adding task and the calculating task or the cancelling task at maximum workload. Thus the Oz beta 2 amplitude was more sensitive to differentiation of task strain between the mental tasks, than the subjective rating. In comparison with the critical levels deduced previously, it was estimated from the Oz beta 2 amplitudes that all the tasks at either workload could induce heavy task strain in the subject, except for the cancelling task at moderate workload. From the subjective ratings, however, it was estimated that no task could induce heavy task strain in the subject. It was, moreover, suggested that the Oz beta 2 amplitudes reflected the difference in the quality of cortical functions and that the subjective ratings of task difficulty were associated with time pressure rather than the quality of cortical functions.     

A prospective study of the psychobehavioral factors responsible for a change from non-patient irritable bowel syndrome to IBS patient status

Background

The literature measuring effects of antidepressant and electroconvulsive therapy (ECT) for major depression on heart rate variability (HRV) in medically well individuals was reviewed.

Methods

Fourteen studies evaluating HRV were included. Twenty three pre-post or within group comparisons were available. Treatment impact on measures of HRV was pooled over studies. We examined different classes of antidepressants, and for short and long electrocardiogram (ECG) recordings separately.

Results

Tricyclic antidepressants (TCAs) were associated with declines in most measures of HRV and significant increase in heart rate (HR) in studies with short recording intervals. No significant changes were found for longer recording times. Treatment effects with selective serotonin reuptake inhibitors (SSRIs) were more variable. Short-recording studies revealed a significant decrease in HR and an increase in one HRV measure. In two 24-hour recording studies no significant changes were observed. No relationship between ECT and HRV has been established in the literature. The effects of other drugs are reported.

Limitations

Few studies measure the effects of treatment of depression on HRV. Existing studies have generally used very small samples, employing a variety of measurements and methodologies.

Conclusion

We confirm that TCAs are associated with a large decrease in HRV and increase HR. However, data for SSRIs is not clear. Although the effect of SSRIs on HRV is weaker than for TCAs, evidence shows that SSRIs are associated with a small decrease in HR, and an increase in one measure of HRV. The use of TCAs in depression leads to changes in HRV that are associated with increased risk of mortality.     

Cost-aware job scheduling for cloud instances using deep reinforcement learning

As the services provided by cloud vendors are providing better performance, achieving auto-scaling, load-balancing, and optimized performance along with low infrastructure maintenance, more and more companies migrate their services to the cloud. Since the cloud workload is dynamic and complex, scheduling the jobs submitted by users in an effective way is proving to be a challenging task. Although a lot of advanced job scheduling approaches have been proposed in the past years, almost all of them are designed to handle batch jobs rather than real-time workloads, such as that user requests are submitted at any time with any amount of numbers. In this work, we have proposed a Deep Reinforcement Learning (DRL) based job scheduler that dispatches the jobs in real time to tackle this problem. Specifically, we focus on scheduling user requests in such a way as to provide the quality of service (QoS) to the end-user along with a significant reduction of the cost spent on the execution of jobs on the virtual instances. We have implemented our method by Deep Q-learning Network (DQN) model, and our experimental results demonstrate that our approach can significantly outperform the commonly used real-time scheduling algorithms.

     

Protein Conformational Changes Are Detected and Resolved Site Specifically by Second-Harmonic Generation

We present here a straightforward, broadly applicable technique for real-time detection and measurement of protein conformational changes in solution. This method is based on tethering proteins labeled with a second-harmonic generation (SHG) active dye to supported lipid bilayers. We demonstrate our method by measuring the conformational changes that occur upon ligand binding with three well-characterized proteins labeled at lysine residues: calmodulin (CaM), maltose-binding protein (MBP), and dihydrofolate reductase (DHFR). We also create a single-site cysteine mutant of DHFR engineered within the Met20 catalytic loop region and study the protein’s structural motion at this site. Using published x-ray crystal structures, we show that the changes in the SHG signals upon ligand binding are the result of structural motions that occur at the labeled sites between the apo and ligand-bound forms of the proteins, which are easily distinguished from each other. In addition, we demonstrate that different magnitudes of the SHG signal changes are due to different and specific ligand-induced conformational changes. Taken together, these data illustrate the potential of the SHG approach for detecting and measuring protein conformational changes for a wide range of biological applications.     

The Effects of Heart Rate Variability (HRV) Biofeedback on HRV Reactivity and Recovery During and After Anger Recall Task for Patients with Coronary Artery Disease

Patients with coronary artery disease (CAD) often experience anger events before cardiovascular events. Anger is a psychological risk factor and causes underlying psychophysiological mechanisms to lose balance of the autonomic nervous system (ANS). The heart rate variability (HRV) was the common index for ANS regulation. It has been confirmed that heart rate variability biofeedback (HRV-BF) restored ANS balance in patients with CAD during the resting state. However, the effects of HRV-BF during and after the anger event remain unknown. This study aimed to examine the effects of HRV-BF on ANS reactivity and recovery during the anger recall task in patients with CAD. This study was a randomized control trial with a wait-list control group design, with forty patients in the HRV-BF group (for six sessions) and 44 patients in the control group. All patients received five stages of an anger recall task, including baseline, neutral recall task, neutral recovery, anger recall task, and anger recovery. HRV reactivity in the HRV-BF group at the post-test was lower than that in the control group. HRV recovery at the post-test in the HRV-BF group was higher than that in the control group. The HRV-BF reduced ANS reactivity during anger events and increased ANS recovery after anger events for CAD patients. The possible mechanisms of HRV-BF may increase total HRV, ANS regulation, and baroreflex activation at anger events for patients with CAD, and may be a suitable program for cardiac rehabilitation.

     

Cryoelectron microscopy analysis of the structural changes associated with human rhinovirus type 14 uncoating

Release of the human rhinovirus (HRV) genome into the cytoplasm of the cell involves a concerted structural modification of the viral capsid. The intracellular adhesion molecule 1 (ICAM-1) cellular receptor of the major-group HRVs and the low-density lipoprotein (LDL) receptor of the minor-group HRVs have different nonoverlapping binding sites. While ICAM-1 binding catalyzes uncoating, LDL receptor binding does not. Uncoating of minor-group HRVs is initiated by the low pH of late endosomes. We have studied the conformational changes concomitant with uncoating in the major-group HRV14 and compared them with previous results for the minor-group HRV2. The structure of empty HRV14 was determined by cryoelectron microscopy, and the atomic structure of native HRV14 was used to examine the conformational changes of the capsid and its constituent viral proteins. For both HRV2 and HRV14, the transformation from full to empty capsid involves an overall 4% expansion and an iris type of movement of viral protein VP1 to open up a 10-A-diameter channel on the fivefold axis to allow exit of the RNA genome. The beta-cylinders formed by the N termini of the VP3 molecules inside the capsid on the fivefold axis all open up in HRV2, but we propose that only one opens up in HRV14. The release of VP4 is less efficient in HRV14 than in HRV2, and the N termini of VP1 may exit at different points. The N-terminal loop of VP2 is modified in both viruses, probably to detach the RNA, but it bends only inwards in HRV2.     

The phrenic component of acute schizophrenia--a name and its physiological reality

Decreased heart rate variability (HRV) was shown for unmedicated patients with schizophrenia and their first-degree relatives, implying genetic associations. This is known to be an important risk factor for increased cardiac mortality in other diseases. The interaction of cardio-respiratory function and respiratory physiology has never been investigated in the disease although it might be closely related to the pattern of autonomic dysfunction. We hypothesized that increased breathing rates and reduced cardio-respiratory coupling in patients with acute schizophrenia would be associated with low vagal function. We assessed variability of breathing rates and depth, HRV and cardio-respiratory coupling in patients, their first-degree relatives and controls at rest. Control subjects were investigated a second time by means of a stress task to identify stress-related changes of cardio-respiratory function. A total of 73 subjects were investigated, consisting of 23 unmedicated patients, 20 healthy, first-degree relatives and 30 control subjects matched for age, gender, smoking and physical fitness. The LifeShirt®, a multi-function ambulatory device, was used for data recording (30 minutes). Patients breathe significantly faster (p<.001) and shallower (p<.001) than controls most pronouncedly during exhalation. Patients'' breathing is characterized by a significantly increased amount of middle- (p<.001), high- (p<.001), and very high frequency fluctuations (p<.001). These measures correlated positively with positive symptoms as assessed by the PANSS scale (e.g., middle frequency: r = 521; p<.01). Cardio-respiratory coupling was reduced in patients only, while HRV was decreased in patients and healthy relatives in comparison to controls. Respiratory alterations might reflect arousal in acutely ill patients, which is supported by comparable physiological changes in healthy subjects during stress. Future research needs to further investigate these findings with respect to their physiological consequences for patients. These results are invaluable for researchers studying changes of biological signals prone to the influence of breathing rate and rhythm (e.g., functional imaging).     

Towards meeting Tinbergen's challenge

In mammals, sex specialization is reflected by differences in brain anatomy and function. Measurable differences are documented in reproductive behavior, cognition, and emotion. We hypothesized that gonadotropin-releasing hormone (GnRH) plays a crucial role in controlling the extent of the brain's sex specificity and that changes in GnRH action during critical periods of brain development, such as puberty, will result in altered sex-specific behavioral and physiological patterns. We blocked puberty in half of the 48 same-sex Scottish mule Texel cross sheep twins with GnRH analog (GnRHa) goserelin acetate every 3 weeks, beginning just before puberty. To determine the effects of GnRHa treatment on sex-specific behavior and emotion regulation in different social contexts, we employed the food acquisition task (FAT) and measurement of heart rate variability (HRV). ANOVA revealed significant sex and sex × treatment interaction effects, suggesting that treated males were more likely to leave their companions to acquire food than untreated, while the opposite effect was observed in females. Concordant results were seen in HRV; treated males displayed higher HRV than untreated, while the reverse pattern was found in females, as shown by significant sex and sex × treatment interaction effects. We conclude that long-term prepubertal GnRHa treatment significantly affected sex-specific brain development, which impacted emotion and behavior regulation in sheep. These results suggest that GnRH is a modulator of cognitive function in the developing brain and that the sexes are differentially affected by GnRH modulation.