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Table 2 Summary of the most related works and current work

From: Cardiac arrhythmia detection using deep learning approach and time frequency representation of ECG signals

Author

Database

Data Input

Approach

Performance

Acc

Sen

Sp

Alfaras et al. [6]

MIT-BIH arrhythmia database

1 D ECG

Ensemble of Echo State Networks

96.8%

92.7%

-

Kishore et al. [8]

MIT-BIH arrhythmia database

1 D ECG

Radial Basis Function Neural Network

98.5%

98.3%

99%

Ting et al. [12]

MIT-BIH arrhythmia database

2D ECG

EfficientNet B0

97.3%

89.55%

89.55%

Bhatia et al. [13]

MIT-BIH arrhythmia database

1D ECG

LSTM + CNN

98.36%

-

94.36%

Karthiga et al. [14]

MIT-BIH arrhythmia database

2D ECG

CNN

91.92%

90.21%

95.18%

Madan et al. [15]

MIT-BIH arrhythmia database

2D ECG

LSTM + CNN

97.3%

97%

98%

Proposed work

MIT-BIH arrhythmia database

2D ECG

ResNet 50

99.2%

99.2%

99.6%