Table 3. Comparison between the related work and the method proposed in this work.

Works	Year	Classes	Methods	ACC, %	P, %	S, %
Jung and Lee (14)	2017	4 beat types	WKNN	96.12	96.12	99.97
Li et al. (10)	2017	6 beat types	GA-BPNN	97.78	97.86	99.54
Kachuee et al. (20)	2018	5 beat types	Deep CNN	93.4	95.1	95.2
Yildirim (17)	2018	5 beat types	DULSTM-WS2	99.25	–	–
Oh et al. (18)	2018	5 beat types	CNN-LSTM	98.10	97.50	98.70
Pandey et al. (21)	2019	5 beat types	CNN	98.3	95.51	86.06
Yildirim et al. (19)	2019	5 beat types	LSTM	99.23	99.00	99.00
Gao et al. (16)	2019	8 beat types	LSTM, FL	99.26	99.26	99.14
Our work	2019	18 beat types	CNN	98.27	60.93	99.95

ACC, accuracy; P, precision; S, sensitivity; WKNN, weighted k-nearest neighbor; GA-BPNN, genetic algorithm-backpropagation neural network; CNN, convolutional neural network; LSTM, long short-term memory; DULSTM-WS2, deep unidirectional LSTM network-based wavelet sequences 2; FL, focal loss.