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Review
. 2018 Jun 9;18(6):1894.
doi: 10.3390/s18061894.

Advances in Photopletysmography Signal Analysis for Biomedical Applications

Jermana L Moraes  1 , Matheus X Rocha  2 , Glauber G Vasconcelos  3 , José E Vasconcelos Filho  4 , Victor Hugo C de Albuquerque  5 , Auzuir R Alexandria  6
Affiliations
Review

Advances in Photopletysmography Signal Analysis for Biomedical Applications

Jermana L Moraes et al. Sensors (Basel). .

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.

Keywords: Internet of Health Things; cardiovascular diseases; health care; heart rate variability; photoplethysmography.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Mortality rates by NTCD per 100,000 habitants, all ages, for region of WHO, 2012 [9].
Figure 2
Figure 2
Comparative of 20 years (1997–2017) of PPG publications. Data were obtained from Web of Science TM using “photoplethysmography” as topic (accessed on 20 February 2018).
Figure 3
Figure 3
PPG signal analysis.
Figure 4
Figure 4
Different measurement points of PTT [45].
Figure 5
Figure 5
Representation of the operation of photoplethysmography sensors for finger application, by transmission (a) and by reflection (b). Adapted from [58].
Figure 6
Figure 6
Working principle of PPG sensors [19].
Figure 7
Figure 7
PPG instrumentation.
See this image and copyright information in PMC

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