Cardiovascular system modeling using windkessel segmentation model based on photoplethysmography measurements of fingers and toes
Background: Photoplethysmography (PPG) contains information about the health condition of the heart and blood vessels. Cardiovascular system modeling using PPG signal measurements can represent, analyze, and predict the cardiovascular system. Methods: This study aims to make a cardiovascular system...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wolters Kluwer Medknow Publications
2022-01-01
|
| Series: | Journal of Medical Signals and Sensors |
| Subjects: | |
| Online Access: | http://www.jmssjournal.net/article.asp?issn=2228-7477;year=2022;volume=12;issue=3;spage=192;epage=201;aulast=Dewi |
| _version_ | 1798038505269493760 |
|---|---|
| author | Ervin Masita Dewi Sugondo Hadiyoso Tati Latifah Erawati Rajab Mengko Hasballah Zakaria Kastam Astami |
| author_facet | Ervin Masita Dewi Sugondo Hadiyoso Tati Latifah Erawati Rajab Mengko Hasballah Zakaria Kastam Astami |
| author_sort | Ervin Masita Dewi |
| collection | DOAJ |
| description | Background: Photoplethysmography (PPG) contains information about the health condition of the heart and blood vessels. Cardiovascular system modeling using PPG signal measurements can represent, analyze, and predict the cardiovascular system. Methods: This study aims to make a cardiovascular system model using a Windkessel model by dividing the blood vessels into seven segments. This process involves the PPG signal of the fingertips and toes for further analysis to obtain the condition of the elasticity of the blood vessels as the main parameter. The method is to find the Resistance, Inductance, and Capacitance (RLC) value of each segment of the body through the equivalent equation between the electronic unit and the cardiovascular unit. The modeling made is focused on PPG parameters in the form of stiffness index, the time delay (△t), and augmentation index. Results: The results of the model simulation using PSpice were then compared with the results of measuring the PPG signal to analyze changes in the behavior of the PPG signal taken from ten healthy people with an average age of 46 years, compared to ten cardiac patients with an average age of 48 years. It is found that decreasing 20% of capacitance value and the arterial stiffness parameter will close to cardiac patients' data. Compared with the measurement results, the correlation of the PPG signal in the simulation model is more than 0.9. Conclusions: The proposed model is expected to be used in the early detection of arterial stiffness. It can also be used to study the dynamics of the cardiovascular system, including changes in blood flow velocity and blood pressure. |
| first_indexed | 2024-04-11T21:41:08Z |
| format | Article |
| id | doaj.art-60583db9b8ce4e6fbe5edf35b73f59c7 |
| institution | Directory Open Access Journal |
| issn | 2228-7477 |
| language | English |
| last_indexed | 2024-04-11T21:41:08Z |
| publishDate | 2022-01-01 |
| publisher | Wolters Kluwer Medknow Publications |
| record_format | Article |
| series | Journal of Medical Signals and Sensors |
| spelling | doaj.art-60583db9b8ce4e6fbe5edf35b73f59c72022-12-22T04:01:35ZengWolters Kluwer Medknow PublicationsJournal of Medical Signals and Sensors2228-74772022-01-0112319220110.4103/jmss.jmss_101_21Cardiovascular system modeling using windkessel segmentation model based on photoplethysmography measurements of fingers and toesErvin Masita DewiSugondo HadiyosoTati Latifah Erawati Rajab MengkoHasballah ZakariaKastam AstamiBackground: Photoplethysmography (PPG) contains information about the health condition of the heart and blood vessels. Cardiovascular system modeling using PPG signal measurements can represent, analyze, and predict the cardiovascular system. Methods: This study aims to make a cardiovascular system model using a Windkessel model by dividing the blood vessels into seven segments. This process involves the PPG signal of the fingertips and toes for further analysis to obtain the condition of the elasticity of the blood vessels as the main parameter. The method is to find the Resistance, Inductance, and Capacitance (RLC) value of each segment of the body through the equivalent equation between the electronic unit and the cardiovascular unit. The modeling made is focused on PPG parameters in the form of stiffness index, the time delay (△t), and augmentation index. Results: The results of the model simulation using PSpice were then compared with the results of measuring the PPG signal to analyze changes in the behavior of the PPG signal taken from ten healthy people with an average age of 46 years, compared to ten cardiac patients with an average age of 48 years. It is found that decreasing 20% of capacitance value and the arterial stiffness parameter will close to cardiac patients' data. Compared with the measurement results, the correlation of the PPG signal in the simulation model is more than 0.9. Conclusions: The proposed model is expected to be used in the early detection of arterial stiffness. It can also be used to study the dynamics of the cardiovascular system, including changes in blood flow velocity and blood pressure.http://www.jmssjournal.net/article.asp?issn=2228-7477;year=2022;volume=12;issue=3;spage=192;epage=201;aulast=Dewicardiovascular systemfinger and toe photoplethysmographyphotoplethysmographystiffness indexwindkessel segmentation model |
| spellingShingle | Ervin Masita Dewi Sugondo Hadiyoso Tati Latifah Erawati Rajab Mengko Hasballah Zakaria Kastam Astami Cardiovascular system modeling using windkessel segmentation model based on photoplethysmography measurements of fingers and toes Journal of Medical Signals and Sensors cardiovascular system finger and toe photoplethysmography photoplethysmography stiffness index windkessel segmentation model |
| title | Cardiovascular system modeling using windkessel segmentation model based on photoplethysmography measurements of fingers and toes |
| title_full | Cardiovascular system modeling using windkessel segmentation model based on photoplethysmography measurements of fingers and toes |
| title_fullStr | Cardiovascular system modeling using windkessel segmentation model based on photoplethysmography measurements of fingers and toes |
| title_full_unstemmed | Cardiovascular system modeling using windkessel segmentation model based on photoplethysmography measurements of fingers and toes |
| title_short | Cardiovascular system modeling using windkessel segmentation model based on photoplethysmography measurements of fingers and toes |
| title_sort | cardiovascular system modeling using windkessel segmentation model based on photoplethysmography measurements of fingers and toes |
| topic | cardiovascular system finger and toe photoplethysmography photoplethysmography stiffness index windkessel segmentation model |
| url | http://www.jmssjournal.net/article.asp?issn=2228-7477;year=2022;volume=12;issue=3;spage=192;epage=201;aulast=Dewi |
| work_keys_str_mv | AT ervinmasitadewi cardiovascularsystemmodelingusingwindkesselsegmentationmodelbasedonphotoplethysmographymeasurementsoffingersandtoes AT sugondohadiyoso cardiovascularsystemmodelingusingwindkesselsegmentationmodelbasedonphotoplethysmographymeasurementsoffingersandtoes AT tatilatifaherawatirajabmengko cardiovascularsystemmodelingusingwindkesselsegmentationmodelbasedonphotoplethysmographymeasurementsoffingersandtoes AT hasballahzakaria cardiovascularsystemmodelingusingwindkesselsegmentationmodelbasedonphotoplethysmographymeasurementsoffingersandtoes AT kastamastami cardiovascularsystemmodelingusingwindkesselsegmentationmodelbasedonphotoplethysmographymeasurementsoffingersandtoes |