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Sensors 2018, 18(6), 1894; https://doi.org/10.3390/s18061894

Advances in Photopletysmography Signal Analysis for Biomedical Applications

1
Programa de Pós-Graduação em Engenharia de Telecomunicações, Instituto Federal de Educação, Ciência e Tecnologia do Ceará, Fortaleza 60040-531, Ceará, Brazil
2
Hospital de Messejana–Dr. Carlos Alberto Studart–Avenida Frei Cirilo, 3480–Messejana, Fortaleza 60846-190, Ceará, Brazil
3
Programa de Pós-Graduação em Informática Aplicada, Laboratório de Bioinformática, Universidade de Fortaleza, Fortaleza 60811-905, Ceará, Brazil
*
Author to whom correspondence should be addressed.
Received: 24 April 2018 / Revised: 27 May 2018 / Accepted: 6 June 2018 / Published: 9 June 2018
(This article belongs to the Special Issue Sensor-based E-Healthcare System: Greenness and Security)
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Abstract

Heart Rate Variability (HRV) is an important tool for the analysis of a patient’s physiological conditions, as well a method aiding the diagnosis of cardiopathies. Photoplethysmography (PPG) is an optical technique applied in the monitoring of the HRV and its adoption has been growing significantly, compared to the most commonly used method in medicine, Electrocardiography (ECG). In this survey, definitions of these technique are presented, the different types of sensors used are explained, and the methods for the study and analysis of the PPG signal (linear and nonlinear methods) are described. Moreover, the progress, and the clinical and practical applicability of the PPG technique in the diagnosis of cardiovascular diseases are evaluated. In addition, the latest technologies utilized in the development of new tools for medical diagnosis are presented, such as Internet of Things, Internet of Health Things, genetic algorithms, artificial intelligence and biosensors which result in personalized advances in e-health and health care. After the study of these technologies, it can be noted that PPG associated with them is an important tool for the diagnosis of some diseases, due to its simplicity, its cost–benefit ratio, the easiness of signals acquisition, and especially because it is a non-invasive technique. View Full-Text
Keywords: heart rate variability; photoplethysmography; cardiovascular diseases; Internet of Health Things; health care heart rate variability; photoplethysmography; cardiovascular diseases; Internet of Health Things; health care
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Moraes, J.L.; Rocha, M.X.; Vasconcelos, G.G.; Vasconcelos Filho, J.E.; de Albuquerque, V.H.C.; Alexandria, A.R. Advances in Photopletysmography Signal Analysis for Biomedical Applications. Sensors 2018, 18, 1894.

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