Medical Cybernetics for Continuous Risk Assessment and Management of Insulin Resistance and Related Complications

Abstract

Individualized precision methods are needed for continuous non-invasive monitoring of state variables of risk indicators not just for early detection of subclinical derangements but also to monitor progress of effect of lifestyle modification and medical therapies throughout lifespan. We envision a cloud based cyber-physical system where input data come from wearable sensors along with frequently or daily use of a body-composition/ hydration-analyzer/ photoplethysmography equipped stand-up scale and these sensor data are used for state space modelling of functioning in four domains with major implications for morbidity/ mortality: 1. Cardiometabolic, 2. Cardiorespiratory, 3. Cardio vegetative, and 4. Cardiovascular functioning. The metrics in these 4 domains allow to draw trajectories into the future and to continuously assess risks of endpoints. At subclinical stage of derangements cloud computing generated feedback on a mobile app may provide for automation and self-improvement to meat daily goals of therapeutic efforts. When abnormalities reach more significant level therapies by health care providers are in order along with continued self-management of modifiable risk factors with behavior modification. This article outlines how a Medical Cybernetics centered approach can be used for continuous risk assessment/ management of insulin resistance and its connected pathological processes such as endovascular inflammation and dysfunction.