Figure 1:
Proposed Architecture
Figure 2:
LSTM Structure
Table 1:
Evaluation Metrices
| SL.NO | Evaluation Metrics | Mathematical Expression |
|---|---|---|
| 01 | Accuracy | |
| 02 | Recall | |
| 03 | Specificity | |
| 04 | Precision | |
| 05 | F1-Score |
Table 2:
Comparative Analysis between the Different Models in ECG signal classification
| Algorithm | Evaluation Metrics (%) | ||||
|---|---|---|---|---|---|
| Accuracy | Precision | recall | Specificity | F1-score | |
| GRU | 91.3% | 90.4% | 90.2% | 89.2% | 89.3% |
| RF | 92.5% | 92.34% | 92.48% | 92.35% | 92.6% |
| DT | 93.4% | 93.7% | 93.1% | 93.2% | 93.0% |
| SVM PROPOSED | 89.0% | 89.9% | 89.78% | 89.68% | 90% |
| MODEL | 99% | 99% | 98.96% | 99.1% | 99% |
Figure 3:
Comparative Assessment with Varying Learning Data Percentages based on (a) testing accuracy, (b) sensitivity, (c) specificity (d) Precision (e) F1-Score