Research Article
Recognition of Ocular Artifacts in EEG Signal through a Hybrid Optimized Scheme
Table 6
Overall performance analysis of the proposed DS-EFO-DCN detection and mitigation model with existing classifiers.
| | Performance measures | NN [15] | SVM [12] | EMCD+DPE-EWA-LWT [38] | DCN [26] | DS-EFO-DCN |
| | Accuracy (%) | 90.7 | 93.6 | 90.2 | 92.1 | 94.4 | | Sensitivity (%) | 94.7 | 94.7 | 92.1 | 93.4 | 92.1 | | Specificity (%) | 90.2 | 93.5 | 90.0 | 91.9 | 94.7 | | Precision | 56.20 | 66.00 | 55.10 | 60.60 | 70.10 | | FPR | 9.70 | 6.40 | 9.90 | 8.00 | 5.20 | | FNR | 5.20 | 5.20 | 7.80 | 6.50 | 7.80 | | NPV | 90.20 | 93.50 | 90.10 | 91.90 | 94.70 | | FDR | 43.70 | 33.90 | 44.80 | 39.30 | 30.10 | | F1-score | 70.50 | 77.80 | 68.90 | 73.50 | 79.50 | | MCC | 68.60 | 75.90 | 66.50 | 71.42 | 77.30 |
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