Glossary

analysis and prediction and serve as "(B) …tools allowing for planning and executing dynamic changes of behavior," as desired by behavior scientists [15, 16]. The desire for a (C) dynamic behavior change model development using self-directed behavioral change strategies can arrive with further development of CPS using control equations like the Hamilton-Jacobi-Bellman equation for dynamic optimized control [20] and with further technologies of artificial intelligence.

Type 2 Diabetes - From Pathophysiology to Modern Management

The main contribution of this chapter to medicine and life science is that it lays out a framework using CPS to observe and monitor long-term SVs of the metabolism including markers of insulin resistance. The CPS approach may point to new and promising directions to find workable solutions to challenges of unhealthy metabolic conditions such as insulin resistance, obesity, prediabetes, metabolic

We provided important supportive evidence for feasibility for our concept of

We would like to express our gratitude for the valuable related discussions with Professor Dr. John Buse, UNC-Chapel Hill. Further, we would like to thank Ilona

The author declares that there is no conflict of interest regarding the publication of this paper. No specific funding was provided for this research. This research was performed as part of the author's employment with Ori Diagnostic Instruments, LLC. The author is the inventor of patent [27] and patent application

[28], and the patent and patent application are owned by Ori Diagnostic

Ori, JD, Ori Diagnostic Instruments, LLC, for editorial help.

CPS for indirectly measuring and predicting the otherwise very-difficult- or impossible-to-measure slow changes of SVs and capture them for the first time noninvasively in freely moving humans in their natural environment outside of a metabolic laboratory setting. Serial fat and weight measurements and energy calculations can help unmask changes of insulin resistance in response to user's diet and exercise habits, providing tools to measure metabolic flexibility which can be used as a surrogate marker for metabolic health. Further, CPS has the potential to estimate cardiorespiratory fitness by indirectly estimating maximum oxygen uptake from measuring heart rate reserve, heart rate variability, and pulse oximetry changes with exercise. CPS is a tool to observe the two major risk factors of CVD at the same time: metabolic health and cardiorespiratory fitness, and therefore the new term cardiometabolic health is justifiable and introduced here to emphasize the two interlinked physiological functions impacting mortality significantly. CPS can enable managed and self-improvement of cardiometabolic health. CPS armed with further technologies of control engineering and artificial intelligence can unleash the potential of digital health to help manage conditions essential to primary care

syndrome, and type 2 diabetes.

and to the public at large.

Acknowledgements

Conflict of interest

Instruments, LLC.

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5. Conclusion

