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- W3203707737 abstract "The multipoint electrocardiogram (ECG) monitoring system is considered to provide convenience in observing the health of patients. But the development of this system by implementing a mesh topology based on the ZigBee protocol still has limitations. When more than one active ECG node sends a data stream, there will be incorrect data or damage due to a failure of synchronization between the user node and the coordinator node. Damaged or incorrect data will negatively affect signal interpretation. Therefore, a mechanism is needed to correct or predict the damaged data. In this study, the method of Expectation-Maximization (EM) and Regression Imputation (RI) was proposed to overcome these problems. Real data from previous studies are the main modalities used in this study. The ECG signal data that has been predicted is then compared with the actual ECG data stored in the main controller memory. Root mean square error (RMSE) is calculated to measure system performance. The simulation was performed on 13 ECG waves, each of them has 1000 samples. The simulation results show that the EM method has a lower predictive error value than the RI method. The average RMSE for the EM and RI methods is 4.77 and 6.63, respectively. The proposed method is expected to be used in the case of multi-node ECG monitoring, especially in the ZigBee application to minimize errors." @default.
- W3203707737 created "2021-10-11" @default.
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- W3203707737 date "2022-04-01" @default.
- W3203707737 modified "2023-09-24" @default.
- W3203707737 title "Data prediction for cases of incorrect data in multi-node ECG monitoring" @default.
- W3203707737 hasPublicationYear "2022" @default.
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