Wearable biosensors for monitoring and as a predictive adjunct for patients at risk for ischemic cardiac-related injury

Abstract

Despite increased attention and preventive efforts, the prevalence of major adverse cardiovascular events continues to rise, resulting in profound concerns for both the individual and the population at large.

Rapidly evolving biotechnologies, micro-computerization, communication, and battery design have led to widespread commercial adoption, use, and dependence on smart devices, and, more recently, biosensors.

Currently worn and carried, smart devices such as mobile phones and smart watches possess impressive computational and communication capabilities, monitoring a variety of biometrics such as heart rate, blood pressure, and cardiac rhythm.

Several promising biomarkers have been identified that are expressed early in the development of cardiac injury.

Biosensors that can assay multiple variants are now described, obviating the limitations generally attributed to dependence upon a single biomarker.

Employing mathematical modeling along with intelligent learning capabilities complements and augments their potential value.

Data derived from wearable multivariate biosensors linked to already worn smart devices can communicate information to protected settings with enhanced computational capability and cogency by evaluating relayed biometrics and early expressed biomarkers as well as trending data, improving sensitivity and specificity.

Integrating intelligent learning capabilities can further power these efforts with beneficial impact on individuals and groups at risk, yielding great promise as monitoring and predictive adjuncts. Future derivations might, for those of particular concern, be linked to critical drug delivery and interventional systems.