Background: There is a need to facilitate efforts to reduce metabolic, cardiovascular, and stressrelated risks with a healthy lifestyle and improve cardio metabolic and cardio-vegetative health and longevity with self-management and guided therapy. We recently introduced a Cyber-Physical System (CPS) to facilitate this process. CPS is a mobile technology integrating sensory data from various mobile devices into individualized dynamic mathematical models of physiological processes, allowing for analysis and prediction and maximizing user control and supported by the primary provider.
Methods: Closely mimicking HOMA-IR (a practical laboratory measurement of insulin resistance) is our metric allowing for the noninvasive observation of insulin resistance changes by estimating R or Rw-ratio which are defined as R=ΔL/ΔF and Rw=ΔW/ΔF where ΔL, ΔW and ΔF are lean mass, weight and fat mass change over 24 hrs. We can estimate R or Rw-ratio either with use of our Self-Adaptive Model of the Energy Metabolism (SAM-HEM) demanding precise calorie counting or with our Weight, Fat weight, Energy balance (WFE) model without mandatory calorie counting by serially measuring weight, fat weight, and energy balance. The verification of this concept was performed using data from 12 clinical studies with 39 clinical study arms and with total number of patients n=2010.
Results: The correlation between changes of HOMA-IR and changes of daily WFE calculated Rw-ratio was -0.6745 with a P value of 0.0000024.
Conclusion: Our cyber-physical system along with a sensor system can provide a truly individualized strategy for estimation, measurement, and prediction of physiological variables of the metabolism including changes of insulin resistance which are essential for prevention and treatment diabetes and cardiovascular disease in primary care.
Published Date: 2024-06-28; Received Date: 2024-05-16
