The Role of Heart Rate Variability in the Future of Remote Digital Biomarkers.

Andrew P Owens

doi:10.3389/fnins.2020.582145

Abstract

Heart rate variability (HRV) offers insights into humoral, neural and neurovisceral processes in health and disorders of brain, body and behavior but has yet to be fully potentiated in the digital age. Remote measurement technologies (RMTs), such as, smartphones, wearable sensors or home-based devices, can passively capture HRV as a nested parameter of neurovisceral integration and health during everyday life, providing insights across different contexts, such as activities of daily living, therapeutic interventions and behavioral tasks, to compliment ongoing clinical care. Many RMTs measure HRV, even consumer wearables and smartphones, which can be deployed as wearable sensors or digital cameras using photoplethysmography. RMTs that measure HRV provide the opportunity to identify digital biomarkers indicative of changes in health or disease status in disorders where neurovisceral processes are compromised. RMT-based HRV therefore has potential as an adjunct digital biomarker in neurovisceral digital phenotyping that can add continuously updated, objective and relevant data to existing clinical methodologies, aiding the evolution of current “diagnose and treat” care models to a more proactive and holistic approach that pairs established markers with advances in remote digital technology.

Highlights

Remote Measurement Technologies (RMTs) refers to, “any mobile technology that enables monitoring of a person’s health status through a remote interface, with the data either transmitted to a healthcare provider for review or to be used as a means of education for the user themselves” (Davis et al, 2014)
Simple monitoring and thresholding of such an individual’s Heart rate variability (HRV) could provide an adjunct “red flag” marker for risk of declining mental health to the patient’s clinical team. Both frequency domain and time domain HRV data inversely relate to IL-6, HF-HRV correlates with many inflammatory markers and poorer HRV predicts C-reactive protein levels and white blood cell counts in healthy adults (Thayer and Fischer, 2009), providing a valuable surrogate measure of inflammation that can potentially be collected remotely over large periods of time and in correlation with other relevant clinical and digital signatures
With the rapid progressive iterations of Remote measurement technologies (RMTs), such an approach could be adopted in a real-world setting, whereby, smartphone-based, home-based or wearable sensors could be deployed for people with epilepsy as they go about their daily lives, to passively collect HRV data that could be combined with other digital biomarkers and clinical profiles to predict acute episodes

Summary

Introduction

Remote Measurement Technologies (RMTs) refers to, “any mobile technology that enables monitoring of a person’s health status through a remote interface, with the data either transmitted to a healthcare provider for review or to be used as a means of education for the user themselves” (Davis et al, 2014). Remote measurement technologies that measure HRV provide the opportunity to identify digital biomarkers indicative of changes in health or disease status in disorders where neurovisceral processes are compromised, such as depression, epilepsy, substance abuse, neurodegeneration, dissociative disorders, and dysautonomia (Thaisetthawatkul et al, 2004; Halaris, 2013; Marhe and Franken, 2014; Eccles et al, 2015; Hyett et al, 2015; Owens et al, 2015).

Results

Conclusion