Name
Title | ||
|---|---|---|
Application of photoplethysmography signals for healthcare systems: An in-depth review |
Abstract | ||
|---|---|---|
Background and objectives: Photoplethysmography (PPG) is a device that measures the amount of light absorbed by the blood vessel, blood, and tissues, which can, in turn, translate into various measurements such as the variation in blood flow volume, heart rate variability, blood pressure, etc. Hence, PPG signals can produce a wide variety of biological information that can be useful for the detection and diagnosis of various health problems. In this review, we are interested in the possible health disorders that can be detected using PPG signals. Methods: We applied PRISMA guidelines to systematically search various journal databases and identified 43 PPG studies that fit the criteria of this review. Results: Twenty-five health issues were identified from these studies that were classified into six categories: cardiac, blood pressure, sleep health, mental health, diabetes, and miscellaneous. Various routes were employed in these PPG studies to perform the diagnosis: machine learning, deep learning, and statistical routes. The studies were reviewed and summarized. Conclusions: We identified limitations such as poor standardization of sampling frequencies and lack of publicly available PPG databases. We urge that future work should consider creating more publicly available databases so that a wide spectrum of health problems can be covered. We also want to promote the use of PPG signals as a potential precision medicine tool in both ambulatory and hospital settings. (C) 2022 Elsevier B.V. All rights reserved. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.cmpb.2022.106677 | COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE |
Keywords | DocType | Volume |
Photoplethysmography (PPG), Deep learning, Machine learning, PRISMA, Cardiac, Blood pressure, Sleep, Mental health, Diabetes, Computer-aided diagnosis (CAD) | Journal | 216 |
ISSN | Citations | PageRank |
0169-2607 | 0 | 0.34 |
References | Authors | |
0 | 9 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hui Wen Loh | 1 | 0 | 1.01 |
| Shuting Xu | 2 | 0 | 0.68 |
| Oliver Faust | 3 | 0 | 0.34 |
| Chui Ping Ooi | 4 | 0 | 1.35 |
| Prabal Datta Barua | 5 | 0 | 0.34 |
| Subrata Chakraborty | 6 | 0 | 0.68 |
| Ru-San Tan | 7 | 0 | 1.01 |
| Filippo Molinari | 8 | 0 | 1.35 |
| Rajendra Acharya U | 9 | 4666 | 296.34 |