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Assessment of Blood Pressure Using Only a Smartphone and Machine Learning Techniques: A Systematic Review

Haugg, Fridolin 1; Elgendi, Mohamed; Menon, Carlo
1 Fakultät für Maschinenbau (MACH), Karlsruher Institut für Technologie (KIT)

Abstract:

Regular monitoring of blood pressure (BP) allows for early detection of hypertension and symptoms related to cardiovascular disease. Measuring BP with a cuff requires equipment that is not always readily available and it may be impractical for some patients. Smartphones are an integral part of the lives of most people; thus, detecting and monitoring hypertension with a smartphone is likely to increase the ability to monitor BP due to the convenience of use for many patients. Smartphones lend themselves to assessing cardiovascular health because their built-in sensors and cameras provide a means of detecting arterial pulsations. To this end, several image processing and machine learning (ML) techniques for predicting BP using a smartphone have been developed. Several ML models that utilize smartphones are discussed in this literature review. Of the 53 papers identified, seven publications were evaluated. The performance of the ML models was assessed based on their accuracy for classification, the mean error measure, and the standard deviation of error for regression. It was found that artificial neural networks and support vector machines were often used. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000148483
Veröffentlicht am 12.07.2022
Originalveröffentlichung
DOI: 10.3389/fcvm.2022.894224
Scopus
Zitationen: 4
Web of Science
Zitationen: 3
Dimensions
Zitationen: 4
Cover der Publikation
Zugehörige Institution(en) am KIT Fakultät für Maschinenbau (MACH)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2022
Sprache Englisch
Identifikator ISSN: 2297-055X
KITopen-ID: 1000148483
Erschienen in Frontiers in Cardiovascular Medicine
Verlag Frontiers Media SA
Band 9
Seiten Art.-Nr.: 894224
Vorab online veröffentlicht am 13.06.2022
Nachgewiesen in Scopus
Web of Science
Dimensions
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