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New Photoplethysmographic Signal Analysis Algorithm for Arterial Stiffness Estimation
The ability to identify premature arterial stiffening is of considerable value in the prevention of cardiovascular diseases. The “ageing index” (AGI), which is calculated from the second derivative photoplethysmographic (SDPPG) waveform, has been used as one method for arterial stiffness estimation...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3747602/ https://www.ncbi.nlm.nih.gov/pubmed/23983620 http://dx.doi.org/10.1155/2013/169035 |
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author | Pilt, Kristjan Ferenets, Rain Meigas, Kalju Lindberg, Lars-Göran Temitski, Kristina Viigimaa, Margus |
author_facet | Pilt, Kristjan Ferenets, Rain Meigas, Kalju Lindberg, Lars-Göran Temitski, Kristina Viigimaa, Margus |
author_sort | Pilt, Kristjan |
collection | PubMed |
description | The ability to identify premature arterial stiffening is of considerable value in the prevention of cardiovascular diseases. The “ageing index” (AGI), which is calculated from the second derivative photoplethysmographic (SDPPG) waveform, has been used as one method for arterial stiffness estimation and the evaluation of cardiovascular ageing. In this study, the new SDPPG analysis algorithm is proposed with optimal filtering and signal normalization in time. The filter parameters were optimized in order to achieve the minimal standard deviation of AGI, which gives more effective differentiation between the levels of arterial stiffness. As a result, the optimal low-pass filter edge frequency of 6 Hz and transitionband of 1 Hz were found, which facilitates AGI calculation with a standard deviation of 0.06. The study was carried out on 21 healthy subjects and 20 diabetes patients. The linear relationship (r = 0.91) between each subject's age and AGI was found, and a linear model with regression line was constructed. For diabetes patients, the mean AGI value difference from the proposed model y (AGI) was found to be 0.359. The difference was found between healthy and diabetes patients groups with significance level of P < 0.0005. |
format | Online Article Text |
id | pubmed-3747602 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-37476022013-08-27 New Photoplethysmographic Signal Analysis Algorithm for Arterial Stiffness Estimation Pilt, Kristjan Ferenets, Rain Meigas, Kalju Lindberg, Lars-Göran Temitski, Kristina Viigimaa, Margus ScientificWorldJournal Research Article The ability to identify premature arterial stiffening is of considerable value in the prevention of cardiovascular diseases. The “ageing index” (AGI), which is calculated from the second derivative photoplethysmographic (SDPPG) waveform, has been used as one method for arterial stiffness estimation and the evaluation of cardiovascular ageing. In this study, the new SDPPG analysis algorithm is proposed with optimal filtering and signal normalization in time. The filter parameters were optimized in order to achieve the minimal standard deviation of AGI, which gives more effective differentiation between the levels of arterial stiffness. As a result, the optimal low-pass filter edge frequency of 6 Hz and transitionband of 1 Hz were found, which facilitates AGI calculation with a standard deviation of 0.06. The study was carried out on 21 healthy subjects and 20 diabetes patients. The linear relationship (r = 0.91) between each subject's age and AGI was found, and a linear model with regression line was constructed. For diabetes patients, the mean AGI value difference from the proposed model y (AGI) was found to be 0.359. The difference was found between healthy and diabetes patients groups with significance level of P < 0.0005. Hindawi Publishing Corporation 2013-08-04 /pmc/articles/PMC3747602/ /pubmed/23983620 http://dx.doi.org/10.1155/2013/169035 Text en Copyright © 2013 Kristjan Pilt et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Pilt, Kristjan Ferenets, Rain Meigas, Kalju Lindberg, Lars-Göran Temitski, Kristina Viigimaa, Margus New Photoplethysmographic Signal Analysis Algorithm for Arterial Stiffness Estimation |
title | New Photoplethysmographic Signal Analysis Algorithm for Arterial Stiffness Estimation |
title_full | New Photoplethysmographic Signal Analysis Algorithm for Arterial Stiffness Estimation |
title_fullStr | New Photoplethysmographic Signal Analysis Algorithm for Arterial Stiffness Estimation |
title_full_unstemmed | New Photoplethysmographic Signal Analysis Algorithm for Arterial Stiffness Estimation |
title_short | New Photoplethysmographic Signal Analysis Algorithm for Arterial Stiffness Estimation |
title_sort | new photoplethysmographic signal analysis algorithm for arterial stiffness estimation |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3747602/ https://www.ncbi.nlm.nih.gov/pubmed/23983620 http://dx.doi.org/10.1155/2013/169035 |
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