The continuous monitoring of physiological parameters has become increasingly common with the emergence of smart wearable devices in these recent years. The evolution towards progressively compact and versatile platforms has contributed to the advancement of Internet of Things (IoT) systems for healthcare, where diagnoses of an individual’s health status are made in real time and in a non-obtrusive way. This paper describes the development of wearable smart sensing platform based on photoplethysmography (PPG) for cardiac activity assessment. The platform provides information about autonomic nervous system in a unobtrusive way through heart rate variability (HRV) analysis. The validation of the proposed system is presented by comparing its HRV measurements with those from an electrocardiography (ECG)-based reference device. Strong correlation results were obtained which underline the capabilities of the developed platform to provide reliable estimation of HRV.

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Internet of things,Photoplethysmography,Biomedical sensor,Heart rate variability,Autonomic nervous system