Please use this identifier to cite or link to this item: http://10.1.7.192:80/jspui/handle/123456789/9160
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dc.contributor.authorBhavsar, Raj-
dc.date.accessioned2020-07-20T06:23:50Z-
dc.date.available2020-07-20T06:23:50Z-
dc.date.issued2019-06-01-
dc.identifier.urihttp://10.1.7.192:80/jspui/handle/123456789/9160-
dc.description.abstractNowadays the Health-care systems are shifted from patient care to monitored care. A motive of this project is the Real-time prediction of Cardiovascular disease using smart watch data and Short term Heart Rate Variability analysis. Therefore here we use clas- sification and regression machine learning algorithms on that data set in which we have implemented the regression algorithms on data set which is created using MI Band 3 with time laps of 10 minutes. Performance matrix for different algorithms is shown and rectify that RNN and SVR algorithm are suitable and giving good results and with respect to data-set, what is the size of data-set matters a lot. Here as we can see the size of the data-set is small so the models are not giving best fit.en_US
dc.publisherInstitute of Technologyen_US
dc.relation.ispartofseries17MCEC03;-
dc.subjectComputer 2017en_US
dc.subjectProject Report 2017en_US
dc.subjectComputer Project Reporten_US
dc.subjectProject Reporten_US
dc.subject17MCEen_US
dc.subject17MCECen_US
dc.subject17MCEC03en_US
dc.titleReal Time Prediction of Heart (Cardiovascular) Disease using Smart Watch Data and Short Term HRV(Heart Rate Variability) Analysisen_US
dc.typeDissertationen_US
Appears in Collections:Dissertation, CE

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