Wearable biosensor systems and resilience: a perfect storm in health care?

Wearable-Measured Sleep and Resting Heart Rate Variability as an Outcome of and Predictor for Subjective Stress Measures: A Multiple N-of-1 Observational Study

The effects of stress may be alleviated when its impact or a decreased stress-resilience are detected early. This study explores whether wearable-measured sleep and resting HRV in police officers can be predicted by stress-related Ecological Momentary Assessment (EMA) measures in preceding days and predict stress-related EMA outcomes in subsequent days. Eight police officers used an Oura ring to collect daily Total Sleep Time (TST) and resting Heart Rate Variability (HRV) and an EMA app for measuring demands, stress, mental exhaustion, and vigor during 15-55 weeks. Vector Autoregression (VAR) models were created and complemented by Granger causation tests and Impulse Response Function visualizations. Demands negatively predicted TST and HRV in one participant. TST negatively predicted demands, stress, and mental exhaustion in two, three, and five participants, respectively, and positively predicted vigor in five participants. HRV negatively predicted demands in two participants, and stress and mental exhaustion in one participant. Changes in HRV lasted longer than those in TST. Bidirectional associations of TST and resting HRV with stress-related outcomes were observed at a weak-to-moderate strength, but not consistently across participants. TST and resting HRV are more consistent predictors of stress-resilience in upcoming days than indicators of stress-related measures in prior days.

Moderation of the Stressor-Strain Process in Interns by Heart Rate Variability Measured with a Wearable and Smartphone App: a Within-Subject Design Using Continuous Monitoring

Background

The emergence of smartphones and wearable sensor technologies enables easy and unobtrusive monitoring of physiological and psychological data related to an individual’s resilience. Heart rate variability (HRV) is a promising biomarker for resilience based on between-subject population studies, but observational studies that apply a within-subject design and use wearable sensors in order to observe HRV in a naturalistic real-life context are needed.

Objective

This study aims to explore whether resting HRV and total sleep time (TST) are indicative and predictive of the within-day accumulation of the negative consequences of stress and mental exhaustion. The tested hypotheses are that demands are positively associated with stress and resting HRV buffers against this association, stress is positively associated with mental exhaustion and resting HRV buffers against this association, stress negatively impacts subsequent-night TST, and previous-evening mental exhaustion negatively impacts resting HRV, while previous-night TST buffers against this association.

Methods

In total, 26 interns used consumer-available wearables (Fitbit Charge 2 and Polar H7), a consumer-available smartphone app (Elite HRV), and an ecological momentary assessment smartphone app to collect resilience-related data on resting HRV, TST, and perceived demands, stress, and mental exhaustion on a daily basis for 15 weeks.

Results

Multiple linear regression analysis of within-subject standardized data collected on 2379 unique person-days showed that having a high resting HRV buffered against the positive association between demands and stress (hypothesis 1) and between stress and mental exhaustion (hypothesis 2). Stress did not affect TST (hypothesis 3). Finally, mental exhaustion negatively predicted resting HRV in the subsequent morning but TST did not buffer against this (hypothesis 4).

Conclusions

To our knowledge, this study provides first evidence that having a low within-subject resting HRV may be both indicative and predictive of the short-term accumulation of the negative effects of stress and mental exhaustion, potentially forming a negative feedback loop. If these findings can be replicated and expanded upon in future studies, they may contribute to the development of automated resilience interventions that monitor daily resting HRV and aim to provide users with an early warning signal when a negative feedback loop forms, to prevent the negative impact of stress on long-term health outcomes.

Triboelectric Nanogenerators for Therapeutic Electrical Stimulation

Current solutions developed for the purpose of in and on body (IOB) electrical stimulation (ES) lack autonomous qualities necessary for comfortable, practical, and self-dependent use. Consequently, recent focus has been placed on developing self-powered IOB therapeutic devices capable of generating therapeutic ES for human use. With the recent invention of the triboelectric nanogenerator (TENG), harnessing passive human biomechanical energy to develop self-powered systems has allowed for the introduction of novel therapeutic ES solutions. TENGs are especially effective at providing ES for IOB therapeutic systems given their bioconformability, low cost, simple manufacturability, and self-powering capabilities. Due to the key role of naturally induced electrical signals in many physiological functions, TENG-induced ES holds promise to provide a novel paradigm in therapeutic interventions. The aim here is to detail research on IOB TENG devices applied for ES-based therapy in the fields of regenerative medicine, neurology, rehabilitation, and pharmaceutical engineering. Furthermore, considering TENG-produced ES can be measured for sensing applications, this technology is paving the way to provide a fully autonomous personalized healthcare system, capable of IOB energy generation, sensing, and therapeutic intervention. Considering these grounds, it seems highly relevant to review TENG-ES research and applications, as they could constitute the foundation and future of personalized healthcare.

Can the vagus nerve serve as biomarker for vata dosha activity?

This 'discussion paper' raises 'provocative questions' to identify physiological systems underlying vata dosha and candidate biomarkers for vata activity. We explained the strong correlations between survival and homeostatic functions of the parasympathetic vagus nerve, and functions governed by the five major sub-types of vata dosha (Praana, Udana, Vyaana, Samaana, and Apana). Four reasons were provided to hypothesize that vagal activity is a reliable candidate biomarker of important vata dosha functions. First, normal vata dosha and the vagus maintain neural, respiratory, and digestive homeostasis, and dysfunctions in both entities cause very similar diseases. Second, vata dosha regulates higher neural functions such as mental health and behaviour, and the 'polyvagal theory' proposes similar functions for the vagus. Third, the similar roles of vata dosha and vagus in maintaining gut homeostasis, suggest that vagal activity in the 'gut-brain' link is a candidate biomarker of pakwashaya (lower gut), a primary regulatory site for vata dosha. Fourth, the vagus is the only vital nerve whose activity can be reliably measured and manipulated. Indeed, vagal nerve stimulation is a USA-FDA approved therapy for certain ailments attributed to impaired vata dosha. No other nerve or dosha, has such multi-functional and life-sustaining properties. These arguments position vagal activity as a suitable candidate biomarker for certain functions of vata dosha.

Challenges and Solutions for Designing and Managing pHealth Ecosystems

For improving quality and safety of healthcare as well as efficiency and efficacy of care processes, health systems turn toward personalized, preventive, predictive, participative precision medicine. The related pHealth ecosystem combines different domains represented by a huge variety of different human and non-human actors belonging to different policy domains, coming from different disciplines. Those actors deploy different methodologies, terminologies, and ontologies, offering different levels of knowledge, skills, and experiences, acting in different scenarios and accommodating different business cases to meet the intended business objectives. Core challenge is the formal representation and management of multiple domains' knowledge. For correctly modeling such systems and their behavior, a system-oriented, architecture-centric, ontology-based, policy-driven approach is inevitable, thereby following established Good Modeling Best Practices. The ISO Interoperability Reference Architecture model and framework offers such approach. The paper describes and classifies the ongoing paradigm changes. It presents requirements and solutions for designing and implementing advanced pHealth ecosystems, thereby correctly adopting and integrating existing pHealth interoperability standards, specifications and projects.

Heart Rate Variability in Dental Science

Dentistry has made progress as a profession by integration with both medicine and other human sciences, especially when it uses empirical metrics to study process and outcome variables. Notably, progress in our understanding of genomic, biomic, and other molecular biological phenomena has been valuable. As has been identified by Drury (1, 2), it is proposed in this commentary that the inclusion of heart rate variability (HRV) as a biomarker of health may further this integrative progress. HRV is derived by various linear and non-linear statistical analyses of the R-R, beat-to-beat ECG interval in microseconds. Over twenty three thousand reports are identified in a recent PubMed search of the term heart rate variability, most of which demonstrate HRV's sensitivity to a wide diversity of physical and psychosocial pathologies. The small literature of dental use of HRV in both assessment and treatment will be selectively reviewed and relevant exemplars for other important health applications of HRV will be discussed. This will lead to a proposed agenda for researching HRV's value to professional dentistry as a human health and wellness profession.

Tele-ICU and Patient Safety Considerations

The tele-ICU is designed to leverage, not replace, the need for bedside clinical expertise in the diagnosis, treatment, and assessment of various critical illnesses. Tele-ICUs are primarily decentralized or centralized models with differing advantages and disadvantages. The centralized model has sufficiently powered published data to be associated with improved mortality and ICU length of stay in a cost-effective manner. Factors associated with improved clinical outcomes include improved compliance with best practices; providing off-hours implementation of the bedside physician's care plan; and identification of and rapid response to physiological instability (initial clinical review within 1 hour) and rapid response to alerts, alarms, or direct notification by bedside clinicians. With improved communication and frequent review of patients between the tele-ICU and the bedside clinicians, the bedside clinician can provide the care that only they can provide. Although technology continues to evolve at a rapid pace, technology alone will most likely not improve clinical outcomes. Technology will enable us to process real or near real-time data into complex and powerful predictive algorithms. However, the remote and bedside teams must work collaboratively to develop care processes to better monitor, prioritize, standardize, and expedite care to drive greater efficiencies and improve patient safety.