Design of a Mobile-App for Non-Invasively Detecting High Blood Cholesterol Using Eye Images

dc.contributor.author Alhasawi, Yaser
dc.contributor.author Mullachery, Balakrishnan
dc.contributor.author Chatterjee, Samir
dc.date.accessioned 2017-12-28T01:49:12Z
dc.date.available 2017-12-28T01:49:12Z
dc.date.issued 2018-01-03
dc.description.abstract Medical research proves that high blood cholesterol is identifiable through the iris portion of the human eyes. Currently, a clinical blood test is the only method used in identifying high cholesterol. This study proposed an IT-based approach to prove the concept of monitoring cholesterol content in the blood using the human irises. We have developed a conceptual framework and a smartphone application aimed at capturing an image of the eye and analyzing it for symptoms associated with high blood cholesterol. This is a break-through innovation for a non-invasive way of finding out blood-cholesterol. The application captures the eye image and necessary metadata from a user. Then, a software code will examine the textural pattern of the eye, thus detecting the presence of high blood cholesterol. The result will be displayed on the user's mobile application. Primarily, the feedback to the user will be either "No" or "Yes" cholesterol content in the blood. The results presented through this app will form the basis for a further medical checkup if necessary.
dc.format.extent 9 pages
dc.identifier.doi 10.24251/HICSS.2018.407
dc.identifier.isbn 978-0-9981331-1-9
dc.identifier.uri http://hdl.handle.net/10125/50295
dc.language.iso eng
dc.relation.ispartof Proceedings of the 51st Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Personal Health Management and Technologies
dc.subject Health informatics, high blood cholesterol, mobile apps, image processing.
dc.title Design of a Mobile-App for Non-Invasively Detecting High Blood Cholesterol Using Eye Images
dc.type Conference Paper
dc.type.dcmi Text
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