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DC Field | Value | Language |
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dc.contributor.author | Bhavsar, Raj | - |
dc.date.accessioned | 2020-07-20T06:23:50Z | - |
dc.date.available | 2020-07-20T06:23:50Z | - |
dc.date.issued | 2019-06-01 | - |
dc.identifier.uri | http://10.1.7.192:80/jspui/handle/123456789/9160 | - |
dc.description.abstract | Nowadays 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.publisher | Institute of Technology | en_US |
dc.relation.ispartofseries | 17MCEC03; | - |
dc.subject | Computer 2017 | en_US |
dc.subject | Project Report 2017 | en_US |
dc.subject | Computer Project Report | en_US |
dc.subject | Project Report | en_US |
dc.subject | 17MCE | en_US |
dc.subject | 17MCEC | en_US |
dc.subject | 17MCEC03 | en_US |
dc.title | Real Time Prediction of Heart (Cardiovascular) Disease using Smart Watch Data and Short Term HRV(Heart Rate Variability) Analysis | en_US |
dc.type | Dissertation | en_US |
Appears in Collections: | Dissertation, CE |
Files in This Item:
File | Description | Size | Format | |
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17MCEC03.pdf | 17MCEC03 | 779.15 kB | Adobe PDF | ![]() View/Open |
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