Biometrics from a Wearable Device Reveals Temporary Effects of COVID-19 Vaccines on Cardiovascular, Respiratory, and Sleep Physiology

Although vaccines against SARS-CoV-2 have been proven safe and effective, transient side-effects lasting 24-48 hours post-vaccination have been reported. To better understand the subjective and objective response to COVID-19 vaccination, we conducted a retrospective analysis on 69619 subscribers to a wrist-worn biometric device (WHOOP Inc, Boston, MA, USA) who received either the AstraZeneca, Janssen/Johnson & Johnson, Moderna, or Pfizer/BioNTech vaccine. The WHOOP device measures resting heart rate (RHR), heart rate variability (HRV), respiratory rate (RR), and sleep architecture, and these physiological measures were normalized to the same day of the week, one week prior to vaccination. Averaging across vaccines, RHR, RR, and percent sleep derived from light sleep were elevated on the first night following vaccination and returned to baseline within four nights post-vaccination. When statistical differences were observed between doses on the first night post-vaccination, larger deviations in physiological measures were observed following the first dose of AstraZeneca and the second dose of Moderna and Pfizer/BioNTech. When statistical differences were observed between age groups or gender on the first night post-vaccination, larger deviations in physiological measures were observed in younger populations and in females (compared to males). When combining self-reported symptoms (fatigue, muscle aches, headache, chills, or fever) with the objectively measured physiological parameters, we found that self-reporting fever or chills had the strongest association with deviations in physiological measures following vaccination. In summary, these results suggest that COVID-19 vaccines temporarily affect cardiovascular, respiratory, and sleep physiology, and that dose, gender, and age affect the physiological response to vaccination.

Anxiety disorders and age-related changes in physiology

Background Anxiety disorders are leading contributors to the global disease burden, highly prevalent across the lifespan and associated with substantially increased morbidity and early mortality. Aims The aim of this study was to examine age-related changes across a wide range of physiological measures in middle-aged and older adults with a lifetime history of anxiety disorders compared with healthy controls. Method The UK Biobank study recruited >500 000 adults, aged 37–73, between 2006 and 2010. We used generalised additive models to estimate non-linear associations between age and hand-grip strength, cardiovascular function, body composition, lung function and heel bone mineral density in a case group and in a control group. Results The main data-set included 332 078 adults (mean age 56.37 years; 52.65% women). In both genders, individuals with anxiety disorders had a lower hand-grip strength and lower blood pressure, whereas their pulse rate and body composition measures were higher than in the healthy control group. Case–control group differences were larger when considering individuals with chronic and/or severe anxiety disorders, and differences in body composition were modulated by depression comorbidity status. Differences in age-related physiological changes between females in the anxiety disorder case group and healthy controls were most evident for blood pressure, pulse rate and body composition, whereas this was the case in males for hand-grip strength, blood pressure and body composition. Most differences in physiological measures between the case and control groups decreased with increasing age. Conclusions Findings in individuals with a lifetime history of anxiety disorders differed from a healthy control group across multiple physiological measures, with some evidence of case–control group differences by age. The differences observed varied by chronicity/severity and depression comorbidity.

Brief Report: Above and Beyond Safety: Psychosocial and Biobehavioral Impact of Autism-Assistance Dogs on Autistic Children and their Families

Autism-Assistance Dogs (AADs) are highly-skilled service animals trained primarily to ensure the safety of an autistic child by preventing elopement and mitigating ‘meltdowns’. Although anecdotal accounts and case-studies have indicated that AADs confer benefits above and beyond safety, empirical support anchored in validated clinical, behavioral, and physiological measures is lacking. To address this gap, we studied children and their families before and after receiving a well-trained AAD using a within-subject, repeated-measures design. Notably, this study is the first to assess change in a biomarker for chronic stress in both autistic children and their parents. Final analyses included pre-/post-AAD data from 11 triads (parent/handler-dog-child) demonstrating significantly positive psychosocial and biobehavioral effects of AADs.

A macroscopic link between interhemispheric tract myelination and cortico-cortical interactions during action reprogramming

Myelination has been increasingly implicated in the function and dysfunction of the adult human brain. Although it is known that axon myelination shapes axon physiology in animal models, it is unclear whether a similar principle applies in the living human brain, and at the level of whole axon bundles in white matter tracts. Here, we hypothesised that in humans, cortico-cortical interactions between two brain areas may be shaped by the amount of myelin in the white matter tract connecting them. As a test bed for this hypothesis, we use a well-defined interhemispheric premotor-to-motor circuit. We combined TMS-derived physiological measures of cortico-cortical interactions during action reprogramming with multimodal myelin markers (MT, R1, R2* and FA), in a large cohort of healthy subjects. We found that physiological metrics of premotor-to-motor interaction are broadly associated with multiple myelin markers, suggesting interindividual differences in tract myelination may play a role in motor network physiology. Moreover, we also demonstrate that myelination metrics link indirectly to action switching by influencing local primary motor cortex dynamics. These findings suggest that myelination levels in white matter tracts may influence millisecond-level cortico-cortical interactions during tasks. They also unveil a link between the physiology of the motor network and the myelination of tracts connecting its components, and provide a putative mechanism mediating the relationship between brain myelination and human behaviour.

Wearable Devices, Smartphones, and Interpretable Artificial Intelligence in Combating COVID-19

Physiological measures, such as heart rate variability (HRV) and beats per minute (BPM), can be powerful health indicators of respiratory infections. HRV and BPM can be acquired through widely available wrist-worn biometric wearables and smartphones. Successive abnormal changes in these indicators could potentially be an early sign of respiratory infections such as COVID-19. Thus, wearables and smartphones should play a significant role in combating COVID-19 through the early detection supported by other contextual data and artificial intelligence (AI) techniques. In this paper, we investigate the role of the heart measurements (i.e., HRV and BPM) collected from wearables and smartphones in demonstrating early onsets of the inflammatory response to the COVID-19. The AI framework consists of two blocks: an interpretable prediction model to classify the HRV measurements status (as normal or affected by inflammation) and a recurrent neural network (RNN) to analyze users’ daily status (i.e., textual logs in a mobile application). Both classification decisions are integrated to generate the final decision as either “potentially COVID-19 infected” or “no evident signs of infection”. We used a publicly available dataset, which comprises 186 patients with more than 3200 HRV readings and numerous user textual logs. The first evaluation of the approach showed an accuracy of 83.34 ± 1.68% with 0.91, 0.88, 0.89 precision, recall, and F1-Score, respectively, in predicting the infection two days before the onset of the symptoms supported by a model interpretation using the local interpretable model-agnostic explanations (LIME).

Best Prosody for News: A Psychophysiological Study Comparing a Broadcast to a Narrative Speaking Style

Studies in different languages have identified a broadcast speaking style, a particular manner that broadcasters have of reading news. This speaking style is characterized by an emphatic intonation with a fast speech rate easily recognizable by listeners. Some authors have stated that messages in this style are not positively perceived by listeners, as it is repetitive and regular, but there is no empirical data to support this conclusion, nor has the style been analyzed with physiological measures. The physiological approach has some advantages, such as a more objective assessment and real-time evaluation. Therefore, this study aims to analyze the effectiveness, adequacy, and physiological response of this broadcast style compared to a narrative pattern. We combined self-report with physiological measures. Fifty-six participants listened to six news pieces in both styles and with two voices, male and female. They had to rate the effectiveness and adequacy of the news while we measured their physiological responses (heart rate and electrodermal activity). The results showed that news conveyed through the broadcast style elicited less cognitive resource allocation and emotional arousal than the narrative pattern, but there were no significant differences in self-report evaluations.

Sensitivity of Physiological Measures of Acute Driver Stress: A Meta-Analytic Review

Background: The link between driving performance impairment and driver stress is well-established. Identifying and understanding driver stress is therefore of major interest in terms of safety. Although many studies have examined various physiological measures to identify driver stress, none of these has as yet been definitively confirmed as offering definitive all-round validity in practice.Aims: Based on the data available in the literature, our main goal was to provide a quantitative assessment of the sensitivity of the physiological measures used to identify driver stress. The secondary goal was to assess the influence of individual factors (i.e., characteristics of the driver) and ambient factors (i.e., characteristics of the context) on driver stress. Age and gender were investigated as individual factors. Ambient factors were considered through the experimental apparatus (real-road vs. driving simulator), automation driving (manual driving vs. fully autonomous driving) and stressor exposure duration (short vs. long-term).Method: Nine meta-analyses were conducted to quantify the changes in each physiological measure during high-stress vs. low-stress driving. Meta-regressions and subgroup analyses were performed to assess the moderating effect of individual and ambient factors on driver stress.Results: Changes in stress responses suggest that several measures are sensitive to levels of driver stress, including heart rate, R-R intervals (RRI) and pupil diameter. No influence of individual and ambient factors was observed for heart rate.Applications and Perspective: These results provide an initial guide to researchers and practitioners when selecting physiological measures for quantifying driver stress. Based on the results, it is recommended that future research and practice use (i) multiple physiological measures, (ii) a triangulation-based methodology (combination of measurement modalities), and (iii) a multifactorial approach (analysis of the interaction of stressors and moderators).

Spatial Sound in a 3D Virtual Environment: All Bark and No Bite?

Although the focus of Virtual Reality (VR) lies predominantly on the visual world, acoustic components enhance the functionality of a 3D environment. To study the interaction between visual and auditory modalities in a 3D environment, we investigated the effect of auditory cues on visual searches in 3D virtual environments with both visual and auditory noise. In an experiment, we asked participants to detect visual targets in a 360° video in conditions with and without environmental noise. Auditory cues indicating the target location were either absent or one of simple stereo or binaural audio, both of which assisted sound localization. To investigate the efficacy of these cues in distracting environments, we measured participant performance using a VR headset with an eye tracker. We found that the binaural cue outperformed both stereo and no auditory cues in terms of target detection irrespective of the environmental noise. We used two eye movement measures and two physiological measures to evaluate task dynamics and mental effort. We found that the absence of a cue increased target search duration and target search path, measured as time to fixation and gaze trajectory lengths, respectively. Our physiological measures of blink rate and pupil size showed no difference between the different stadium and cue conditions. Overall, our study provides evidence for the utility of binaural audio in a realistic, noisy and virtual environment for performing a target detection task, which is a crucial part of everyday behaviour—finding someone in a crowd.

Impacts of Color Coding on Programming Learning in Multimedia Learning: Moving Toward a Multimodal Methodology

In the present study, we tested the effectiveness of color coding on the programming learning of students who were learning from video lectures. Effectiveness was measured using multimodal physiological measures, combining eye tracking and electroencephalography (EEG). Using a between-subjects design, 42 university students were randomly assigned to two video lecture conditions (color-coded vs. grayscale). The participants’ eye tracking and EEG signals were recorded while watching the assigned video, and their learning performance was subsequently assessed. The results showed that the color-coded design was more beneficial than the grayscale design, as indicated by smaller pupil diameter, shorter fixation duration, higher EEG theta and alpha band power, lower EEG cognitive load, and better learning performance. The present findings have practical implications for designing slide-based programming learning video lectures; slides should highlight the format of the program code using color coding.