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James L Fozard, William D Kearns, Linking Longitudinal Variability in Physiological and Behavioral Data to Disease Processes: Opportunities and Challenges, Public Policy & Aging Report, Volume 27, Issue 2, 2017, Pages 62–67, https://doi.org/10.1093/ppar/prx012
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As stated by Shameer and colleagues (2017), “monitoring and modeling biomedical, health care and wellness data from individuals and converging data on a population scale have tremendous potential to improve understanding of the transition to the healthy state of human physiology to disease setting” (p.105). Shameer et al. (2017) have reviewed translational bioinformatics methods, tools, and resources, and provide an excellent summary of health-monitoring devices and their application to individualized diagnostics, prognosis, and clinical or wellness interventions. The opportunities they envision are advances in real-time biomedical and healthcare analytics in the clinical setting that will be driven by technologies that monitor, store, remotely transmit, analyze, and display everyday physiological and behavioral data in both healthy and disease states. A broad goal of these technologies is to obtain longitudinal measures in natural settings. “Big Data” analytics applied to masses of streamed sensor data and electronic health records are important tools for effectively realizing the opportunities presented by new monitoring technologies. The applications discussed extend well beyond existing telemedicine functions, in which clinical interactions and physiological and behavioral data traditionally accrued in clinical settings are gathered instead at significant distances using remote sensing.
