Table 2 Performance and accuracy of the fatigue driving detection model
From: Fatigue driving detection based on electrooculography: a review
No. of references | Model | Publication | Accuracy |
|---|---|---|---|
5 | Finite-state machine (FSM) | IET science, measurement and technology | 99% |
10 | Support vector machine (SVM) | Expert systems with application | 86.67% |
16 | Support vector machine (SVM) | Biomedical signal processing and control | 86 ± 3% |
19 | Support vector machine (SVM) | Automation in construction | 85.0% |
25 | Bayes classifier (BL) | Medical engineering and physics | 83.40% |
29 | Relevant vector machine (RVM) | IEEE access | 99.1 ± 1.2% |
31 | Fuzzy and neuro fuzzy based (NF) | IEEE transactions on systems, man, and cybernetics—part a: systems and humans | 80.6% |
32 | Discriminative graph regularized extreme learning machine (GELM) | 2014 International joint conference on neural networks | 91.8% |
33 | Support vector machine (SVM) | IEEE transactions on pattern analysis and machine intelligence | 76.1% |
36 | Inductive rule based (IR) | Biomed. Signal Process. Control | 96.7% |
38 | Support vector machine (SVM) | Biomedical signal processing and control | 79.6% |
49 | Support vector machine (SVM) | IEEE access | 89.96% |
50 | Artificial neural network (ANN) | IEEE transactions on intelligent transportation systems | 96.5% ~ 99.5% |
53 | Discriminative graph regularized extreme learning machine (GELM) | 2016 international joint conference on neural networks (IJCNN) | 80.80% |
54 | Artificial neural network (ANN) | 2017 8th International IEEE/EMBS conference on neural engineering (NER) | 85.0% |
55 | Fuzzy and neuro fuzzy based (NF) | IEEE transactions on biomedical engineering | 91.5% |
56 | kernel principal component analysis (KPCA) and support vector machine (SVM) | Expert Syst. Appl | 90.04% |
58 | Artificial neural network (ANN) | Medical and biological engineering and computing | 93.75% |
59 | Support vector machine (SVM) | IEEE transactions on biomedical engineering | 95% ~ 97% |
64 | Artificial neural network (ANN) | IEEE transactions on neural systems and rehabilitation engineering | 85.0% |
65 | Inductive rule based (IR) | IEEE access | 74% |
66 | Clustering (CL) | Automation in construction | 93.0% |
67 | Mixed-effect ordered logit model | Analytic methods in accident research | 62.84% |
69 | Adaptation regularization based transfer learning (ARTL) | Expert systems with applications | 94.44% |
72 | Support vector machine (SVM) | Expert systems with applications | 93.0% |
75 | Fuzzy support vector machine (FSVM) | Artificial intelligence in medicine | 90.12 ~ 92.20% |
76 | Artificial neural network (ANN) and Support Vector Machine (SVM) | Expert systems with applications | 94.44% |
77 | Bayes classifier (BL) | Biomedical signal processing and control | 92.0% |
80 | Extremely learning machine (ELM) | Cognitive systems research | 95.71% |