{"title":"UbiHeart: A novel approach for non-invasive blood pressure monitoring through real-time facial video","authors":"Kazi Shafiul Alam, Sayed Mashroor Mamun, Masud Rabbani, Parama Sridevi, Sheikh Iqbal Ahamed","doi":"10.1016/j.smhl.2024.100473","DOIUrl":null,"url":null,"abstract":"<div><p>Monitoring blood pressure (BP) is an essential component of evaluating cardiovascular health, aiding in the early detection and management of hypertension-related complications. Traditional methods of BP measurement often involve invasive or cumbersome devices, leading to discomfort and reduced compliance. We propose a framework to monitor BP non-invasively, analyzing the face video captured by a webcam or smartphone camera leveraging the relationship of image-based Pulse Transit Time (iPTT) and Heart Rate Variability (HRV) with BP. We have built a dataset of 90 sets of collected videos using a mobile phone front camera and BP data from a standard digital BP monitor from 12 individuals from an approved Institutional Review Board (IRB) to evaluate our system. We have got a Mean Absolute Error (MAE) of <span><math><mrow><mn>10</mn><mo>.</mo><mn>35</mn><mo>+</mo><mo>/</mo><mo>−</mo><mn>2</mn><mo>.</mo><mn>5</mn></mrow></math></span> mmHg for systolic BP (SBP) and <span><math><mrow><mn>7</mn><mo>.</mo><mn>8</mn><mo>+</mo><mo>/</mo><mo>−</mo><mn>1</mn><mo>.</mo><mn>5</mn></mrow></math></span> mmHg for diastolic BP (DBP) while using the HRV representation RMSSD. On the other hand, an MAE of <span><math><mrow><mn>8</mn><mo>.</mo><mn>25</mn><mo>+</mo><mo>/</mo><mo>−</mo><mn>3</mn><mo>.</mo><mn>5</mn></mrow></math></span> mmHg for SBP and <span><math><mrow><mn>7</mn><mo>.</mo><mn>7</mn><mo>+</mo><mo>/</mo><mo>−</mo><mn>2</mn><mo>.</mo><mn>5</mn></mrow></math></span> mmHg for DBP while using the HRV representation SDRR. Finally, we have developed a framework and built a real-time system to monitor BP as a mobile and web-based application that can facilitate early detection of trends and anomalies, allowing healthcare providers to intervene promptly and personalize treatment plans.</p></div>","PeriodicalId":37151,"journal":{"name":"Smart Health","volume":"32 ","pages":"Article 100473"},"PeriodicalIF":0.0000,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Smart Health","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352648324000291","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Health Professions","Score":null,"Total":0}
引用次数: 0
Abstract
Monitoring blood pressure (BP) is an essential component of evaluating cardiovascular health, aiding in the early detection and management of hypertension-related complications. Traditional methods of BP measurement often involve invasive or cumbersome devices, leading to discomfort and reduced compliance. We propose a framework to monitor BP non-invasively, analyzing the face video captured by a webcam or smartphone camera leveraging the relationship of image-based Pulse Transit Time (iPTT) and Heart Rate Variability (HRV) with BP. We have built a dataset of 90 sets of collected videos using a mobile phone front camera and BP data from a standard digital BP monitor from 12 individuals from an approved Institutional Review Board (IRB) to evaluate our system. We have got a Mean Absolute Error (MAE) of mmHg for systolic BP (SBP) and mmHg for diastolic BP (DBP) while using the HRV representation RMSSD. On the other hand, an MAE of mmHg for SBP and mmHg for DBP while using the HRV representation SDRR. Finally, we have developed a framework and built a real-time system to monitor BP as a mobile and web-based application that can facilitate early detection of trends and anomalies, allowing healthcare providers to intervene promptly and personalize treatment plans.