Rekabentuk sistem pengecaman puncak isyarat elektrokardiogram menggunakan rangkaian hmlp berbilang untuk mendiagnosis kecacatan jantung

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dc.contributor.authorSyed Hassan, Syed Sahal Hazli Alhady
dc.date.accessioned2015-06-24T00:56:51Z
dc.date.available2015-06-24T00:56:51Z
dc.date.issued2006
dc.description.abstractECG is a heart status analysis system used by cardiologist to interprets which is cheap, effective, easy for implementation and safe to be used. The signal acquisition hardware has been developed according to the standard for ECG signals acquisition. In this research, suitable threshold for preprocessing of the signals was determined in two stages (recognition of peaks aiid elimination of noisy peaks). The preprocessing stage has successfully eliminated 92.71% of the noisy peaks from the ECG signals. MHMLP network has been proposea in tRis research, to increase the performance in identifying peaks (P, Q, R, S and T) of the ECG signals. By utilising the features selection approach, the optimum peaks identification performance of the neural networks system has been determined. From the implementation, the MSE of MHMLP network to identify peaks of ECG signals has been recorded at -27.92d8. As a whole, MHMLP network has achieved recognition performance of 83.78% and 89% during testing and training phase respectively. In order to test the validity of the neural network approach in identifying ECG peaks, and diagnosing the occurrence of heart disorder, an implementation on pediatric patient with LVH was conducted. A total of 119 cases of pediatric patient with L VH and 119 normal cases were used. Six features based on parameter achieved during peak recognition process of ECG signal (P, Q, R, S and T) were used as inputs to the HMLP network. The results of the diagnosis analysis show that false positive is 5.08% and false negative is 3.39% during the testing phase. Sensitivity and specificity during the training phase are perfect (100%}, while 96.55% and 95% are acquired during testing phase respectively. The network performance is perfect (100%) during training phase, while the performance during testing phase is 95.76%.en_US
dc.identifier.urihttp://hdl.handle.net/123456789/808
dc.language.isootheren_US
dc.subjectPengecaman puncaken_US
dc.subjectMendiagnosis kecacatan jantungen_US
dc.titleRekabentuk sistem pengecaman puncak isyarat elektrokardiogram menggunakan rangkaian hmlp berbilang untuk mendiagnosis kecacatan jantungen_US
dc.typeThesisen_US
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