a remote medical monitoring system for heart failure prognosis
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2015
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Abstract
Remote monitoring of heart disease provides the means to keep patients under continuous supervision. In this paper, we introduce the design and implementation of a remote monitoring medical system for heart failure prediction and management. The three-part system includes a patient-end for data collection, a medical data center as data storage and analysis, and a doctor-end to diagnosis and intervention. The main objective of the system is to prognose the occurrence risk of heart failure (HF) confirmed by the level of N-terminal prohormone of brain natriuretic peptide (NT-proBNP) based on the changes of the patients’ (systolic and diastolic) blood pressure and body weight that are measured noninvasively in a home environment. The prediction of HF and non-HF patients was achieved by
a structured support vector machine (SVM) classification algorithm. With the present system, we also proposed a
scoring method to interpret the long-term risk of HF. We demonstrated the efficiency of the system with a pilot
clinical study of 34 samples, where the NT-proBNP test was used to help train the prediction model as well as
check the prediction results for our system. Results showed an accuracy of 79.4% for predicting HF on day 7 based
on daily body weight and blood pressure data acquired over 30 days.
| Reference Key |
zhang2015mobilea
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|---|---|
| Authors | ;Liangqing Zhang;Cuirong Yu;Chunrong Jin;Dajin Liu;Zongwen Xing;Qian Li;Zhinan Li;Qin Li;Yingxiao Wu;Jie Ren |
| Journal | ui sahak |
| Year | 2015 |
| DOI |
10.1155/2015/406327
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| URL | |
| Keywords |
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