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Robust algorithm for arrhythmia classification in ECG using extreme learning machine
Robust algorithm arrhythmia classification ECG extreme learning machine
2010/2/25
The experimental results of the entire MIT-BIH arrhythmia database demonstrate that the performances of the proposed algorithm are 98.00% in terms of average sensitivity, 97.95% in terms of average sp...
Cardiac arrhythmia classification using autoregressive modeling
Cardiac arrhythmia classification autoregressive modeling
2010/3/1
AR modeling results showed that an order of four was sufficient for modeling the ECG signals. The accuracy of detecting NSR, APC, PVC, SVT, VT and VF were 93.2% to 100% using the GLM based classificat...