A Review of Digital Health and Biotelemetry: Modern Approaches towards Personalized Medicine and Remote Health Assessment

Figures

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  Figure 1. Relationship between artificial intelligence, machine learning, and deep learning. Adapted from an open-access source [33].

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  Figure 2. Block diagram of a biotelemetry system. Created based on information from [18,37].

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  Figure 3. Classification of biotelemetry devices. Created based on information from literature references [36,38].

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  Figure 4. Schematic summary of the roles of wearable sensor technology and predictive analytics for monitoring COVID-19. (a) Physiological metrics currently capable of being measured from commercial wearable sensors. (b) Changes in physiological metrics that can be inputted into an early detection algorithm for COVID-19 monitoring to ensure that the true positive rate is robust to support the use of the analytics for real-time clinical decision making. (c) Uses of integrated analytics in monitoring COVID-19 for individual or population health. Abbreviations: HRV—heart rate variability; Resp Rate—respiration rate; SpO2—blood oxygen saturation; Temp—temperature; TP—true positive; FP—false positive; TN—true negative; FN—false negative. Adapted from an open-access source [116].