In the last few years, interest in wearable technology for physiological signal monitoring is rapidly growing, especially during and after the COVID-19 pandemic [1,2,3]. Specifically, considering that heart disease is the leading cause of death globally, continuous monitoring of cardiovascular dynamics has crucial relevance to improving prevention and diagnosis. Photoplethysmography (PPG) is a popular, non-invasive, and low-cost optical technique that can provide useful information about the cardiovascular system, aiming to reveal autonomic dysfunctions and peripheral vascular diseases during daily life. In fact, due to its simplicity and versatility, this technology can be used to develop wearable and wireless devices for out-of-hospital monitoring of both healthy and pathological subjects. Even if technology has successfully increased the comfort of PPG sensors, in terms of wearability, dimensions and battery life, scientific research is still working on several issues, e.g., poor sensor contact, which leads to acquiring signals corrupted by noise and motion artifacts, especially during physical activity [4]. In this context, there are still many challenges related to PPG wearable device design and signal processing techniques to derive robust indices. Furthermore, recent studies have shed light on the possibility of extracting a good surrogate of PPG signal from face RGB video processing, opening the door to not only wireless but also contactless monitoring. For this reasons, the investigation of reliable PPG-derived parameters, including rhythm and morphology features, but also heart rate variability descriptors, is growing in interest, comprising novel signal processing methodologies for artifact removal and feature extraction. This Special Issue focused on original research papers dealing with hardware and software advances in the development of robust and reliable biomarkers for the non-invasive monitoring of cardiovascular dynamics based on PPG signal acquisition. Topics of interest for PPG signal applications included clinical pathologies, biometry, sleep and sport monitoring.

Advances in Wearable Photoplethysmography Applications in Health Monitoring

Nardelli M.
Primo
;
2023-01-01

Abstract

In the last few years, interest in wearable technology for physiological signal monitoring is rapidly growing, especially during and after the COVID-19 pandemic [1,2,3]. Specifically, considering that heart disease is the leading cause of death globally, continuous monitoring of cardiovascular dynamics has crucial relevance to improving prevention and diagnosis. Photoplethysmography (PPG) is a popular, non-invasive, and low-cost optical technique that can provide useful information about the cardiovascular system, aiming to reveal autonomic dysfunctions and peripheral vascular diseases during daily life. In fact, due to its simplicity and versatility, this technology can be used to develop wearable and wireless devices for out-of-hospital monitoring of both healthy and pathological subjects. Even if technology has successfully increased the comfort of PPG sensors, in terms of wearability, dimensions and battery life, scientific research is still working on several issues, e.g., poor sensor contact, which leads to acquiring signals corrupted by noise and motion artifacts, especially during physical activity [4]. In this context, there are still many challenges related to PPG wearable device design and signal processing techniques to derive robust indices. Furthermore, recent studies have shed light on the possibility of extracting a good surrogate of PPG signal from face RGB video processing, opening the door to not only wireless but also contactless monitoring. For this reasons, the investigation of reliable PPG-derived parameters, including rhythm and morphology features, but also heart rate variability descriptors, is growing in interest, comprising novel signal processing methodologies for artifact removal and feature extraction. This Special Issue focused on original research papers dealing with hardware and software advances in the development of robust and reliable biomarkers for the non-invasive monitoring of cardiovascular dynamics based on PPG signal acquisition. Topics of interest for PPG signal applications included clinical pathologies, biometry, sleep and sport monitoring.
2023
Nardelli, M.; Bailon, R.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1215451
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