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Cited by 292Non-Invasive Vital Sign MonitoringHeart Rate Variability and Autonomic ControlECG Monitoring and Analysis

The DOI matches its Crossref record; 134 of the 136 references it cites were found in a registry or an index.

Advances in Photopletysmography Signal Analysis for Biomedical Applications

Open access
Moraes, Jermana L., Rocha, Matheus X., Vasconcelos, Glauber G., Vasconcelos Filho, José E., De Albuquerque, Victor Hugo C., Alexandria, Auzuir R.·2018·Sensors
DOI 10.3390/s18061894PMC PMC6022166
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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.

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Crossref · 10.3390/s18061894

Cites

134 of 134 references verified0 citation errors · 0 not checkable

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Figures

Figure 1 Mortality rates by NTCD per 100,000 habitants, all ages, for region of WHO, 2012 [9].
Figure 1 Mortality rates by NTCD per 100,000 habitants, all ages, for region of WHO, 2012 [9].CC BY · PubMed Central
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 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).CC BY · PubMed Central
Figure 3 PPG signal analysis.
Figure 3 PPG signal analysis.CC BY · PubMed Central
Figure 4 Different measurement points of PTT [45].
Figure 4 Different measurement points of PTT [45].CC BY · PubMed Central
Figure 5 Representation of the operation of photoplethysmography sensors for finger application, by transmission (a) and by reflection (b). Adapted from [58].
Figure 5 Representation of the operation of photoplethysmography sensors for finger application, by transmission (a) and by reflection (b). Adapted from [58].CC BY · PubMed Central
Figure 6 Working principle of PPG sensors [19].
Figure 6 Working principle of PPG sensors [19].CC BY · PubMed Central
Figure 7 PPG instrumentation.
Figure 7 PPG instrumentation.CC BY · PubMed Central

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Citations

Cites

Show all 136 references

Research works printed but not linked: 9

  1. Paschoal, 2003, Controle autonômico cardíaco durante a execução de atividade física dinâmica de baixa intensidade, Rev. Soc. Cardiol. Estado de São Paulo, 13, S1
  2. Corrêa, L.A.F. (2006). Sistema não Invasivo de Monitorização da Pressão Arterial e da Onda de Pulso Utilizando a Fotopletismografia. [Ph.D. Thesis, Programa de Pós Graduação em Engenharia Biomédica, Universidade Federal do Rio de Janeiro, UFRJ].
  3. Kilsztajn, 2003, Health services, expenses and aging of the Brazilian population, Rev. Bras. Study Popul., 20, 93
  4. Martins, R.M.S. (2010). Fotopletismografia para Monitorização Cardí­aca para aplicação no Pulso. [Master’s Thesis, Universidade de Coimbra].
  5. Khaled, 2006, Employing Time-Domain Methods and Poincaré Plot of Heart Rate Variability Signals to Detect Congestive Heart Failure, BIME J., 6, 35
  6. Puri, C., Ukil, A., Bandyopadhyay, S., Singh, R., Pal, A., and Mandana, K. (2016, January 25–30). iCarMa: Inexpensive Cardiac Arrhythmia Management–An IoT Healthcare Analytics Solution. Proceedings of the First IoT of Health ’16 Workshop on IoT-enabled Healthcare and Wellness Technologies and Systems, Singapore.
  7. Pantoni, 2007, Study of heart rate autonomic modulation at rest in elderly patients with chronic obstructive pulmonary disease, Braz. J. Phys. Ther., 11, 35
  8. Vilhegas, L.Z. (2007). Development of a Prototype for Monitoring Oxygen Saturation and Heart Rate for Rodents. [Master’s Thesis, Título de Engenharia Elétrica, Escola Politécnica].
  9. Rodrigues, 2018, Enabling Technologies for the Internet of Health Things, IEEE Access, 6, 13129, 10.1109/ACCESS.2017.2789329 · DOI

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Metadata

Authors
Moraes, J. L., Rocha, M. X., Vasconcelos, G. G., Vasconcelos Filho, J. E., De Albuquerque, V. H. C., & Alexandria, A. R.
Affiliations
  • Instituto Federal de Educação, Ciência e Tecnologia do Ceará (BR)
  • Hospital de Messejana (BR)
  • Programa de Pós-Graduação em Informática Aplicada, Laboratório de Bioinformática, Universidade de Fortaleza, Fortaleza 60811-905, Ceará, Brazil
ORCID
Venue
Sensors
Publisher
MDPI AG
Published
2018-06-09
Volume
18
Issue
6
Pages
1894
ISSN
1424-8220 (ISSN-L)
DOI
10.3390/s18061894
PMC
PMC6022166
OpenAlex
W2808345783
Cited by
292
References
136
Citations by year
2026: 12 · 2025: 31 · 2024: 37 · 2023: 38 · 2022: 49 · 2021: 46 · 2020: 38 · 2019: 38 · 2018: 3
FWCI
2.55
Type
journal article
Language
en
Open access
Licence
Locations
  • Sensors (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Conselho Nacional de Desenvolvimento Científico e Tecnológico (304315/2017-6)
  • Fundação Cearense de Apoio ao Desenvolvimento Científico e Tecnológico (no number)
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
Keywords
photoplethysmography, heart rate variability, PPG signal analysis, cardiovascular disease diagnosis, non-invasive monitoring, PPG sensor, Internet of Medical Things, artificial intelligence, genetic algorithm, biosensors, e-health, Internet of Things
MeSH terms
Blood Pressure, Heart Rate, Humans, Signal Processing, Computer-Assisted, Photoplethysmography, Telemedicine

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