Heart rate variability (HRV) is increasingly recognized as a central variable of interest in health maintenance, disease prevention and performance optimization. It is also a sensitive biomarker of health status, disease presence and functional abilities, acquiring and processing high fidelity inter beat interval data, along with other psychophysiological parameters that can assist in clinical assessment and intervention, population health studies/digital epidemiology and positive performance optimization. We describe a system using high-throughput artificial intelligence based on the KUBIOS platform to combine time, frequency and nonlinear data domains acquired by wearable or implanted biosensors to guide in clinical assessment, decision support and intervention, population health monitoring and individual self-regulation and performance enhancement, including the use of HRV biofeedback. This approach follows the iP4 health model which emphasizes an integral, personalized, predictive, preventive and participatory approach to human health and well-being. It therefore includes psychological, biological, genomic, sociocultural, evolutionary and spiritual variables as mutually interactive elements in embodying complex systems adaptation.
Part of the book: Autonomic Nervous System Monitoring
While the important role of the autonomic nervous system (ANS) has been historically underappreciated, recently there has been a rapid proliferation of empirical, methodological and theoretical progress in our more detailed understanding of the ANS. Previous more simplistic models of the role of the ANS using the construct of homeostasis have been enhanced by the use of the construct of allostasis and a wide variety of technological innovations including wearable and implantable biosensors have led to improved understanding of both basic and applied knowledge. This chapter will explore in particular heart rate variability (HRV) as a rich variable which has developed an extensive literature, beginning with predicting all-cause mortality, but now encompassing a wide variety of disease and illness states; cognitive, affective and behavioral processes and performance optimization. A critical analysis of HRV from the perspective of complex adaptive systems and non-linear processes will be included and innovative future uses of HRV will be described.
Part of the book: Autonomic Nervous System
Edge computation (EC) will be explored from the viewpoint of complex systems. An evolutionary and ecological context will be described in detail, including the subjects of epigenetics, self-domestication, attachment theory, scientific cosmology, deep learning, and other artificial intelligence issues and the role of wireless data acquisition analysis and feedback. A technical exemplar will be described and examples of potential integration with various systems such as public health and epidemiology, clinical medicine, operations, and fitness will be proposed. Also, various system vulnerabilities and failures will be discussed and policy implications in the global and clinical health and wellness domains will be identified.
Part of the book: Edge Computing