| Reference | Task | Feature | Classification algorithm | Number of classification | Classificationaccuracy |
|---|
| Ref.[93], 2015 | MA and other 11 mental tasks | Slope of HbO, HbR and HbT, etc. | LDA | 2 | 77%(personalized tasks);73%(prescribed tasks) | | Ref.[94], 2015 | MA and mental counting | Mean of HbO and HbR | SVM | 2 | 82.4%(the best) | | Ref.[95], 2015 | MA, word generation, mental rotation, and rest | Slope of HbO and HbR | DNN, LDA, and SLDA | 2 | DNN: 63.2%; LDA: 64.3%; SLDA: 65.7% | | Ref.[96], 2015 | Active and passive movements of fingers of the right hand | Average level of HbO and spatial patterns | SVM | 2 | 71.82% | | Ref.[97], 2017 | MI and ME(hand extension and finger tapping) | Mean, slope, quadratic coefficient, and approximate entropy of HbO | SVM | 4 | 87.65%(hand extension); 87.58%(finger tapping) | | Ref.[82], 2016 | MA and rest | Mean, peak, slope, variance, kurtosis, and skewness of HbO | LDA, QDA, KNN, NBC, SVM, and ANN | 2 | 71.6%, 90.0%, 69.7%, 89.8%, 89.5%, and 91.4%(2D features); 79.6%, 95.2%, 64.5%, 94.8%, 95.2%, and 96.3%(3D features) | | Ref.[98], 2017 | ME of left and right hand(hand grasping) | Approximation coefficients of EEG and mean of HbO and HbR | SVM | 2 | 91.02% | | Ref.[99], 2017 | Visual task of primary RGB colors | Mean, peak, slope, skewness, and kurtosis of HbO | LDA | 3 | 55.29% | | Ref.[71], 2017 | MI of left and right hand | Mean,slope, and variance of HbO and HbR | LDA | 2 | 75.3%(HbO); 72.3%(HbR) | | Ref.[100], 2017 | Handshake, ball grasp, poking, and cold temperature stimulation | Mean, peak, and skewness of HbO | LDA | 2 and 4 | Binary: 78.12%, 75.94%; quaternary: 50.31% | | Ref.[87], 2017 | ME of left and right hand and rest | Mean, peak,slope, variance, kurtosis, and skewness of HbO and HbR | SVM, ANN, and CNN | 3 | SVM: 86.19%; ANN: 89.35%; CNN: 92.68% | | Ref.[101], 2018 | ME of finger tapping | Mean and slope of HbO and HbR | LDA and GLM | 2 | LDA: 78.7%; GLM: 65.76%(HbO),70.3%(HbR) | | Reference | Task | Feature | Classification algorithm | Number of classification | Classificationaccuracy | | Ref.[72], 2018 | MA and rest | Mean and variance of HbO and HbR | LDA | 2 | 77.2%(HbO); 72.9%(HbR) | | Ref.[77], 2018 | Stroop task | Wavelet energy of HbO | SVM | 2 | 87.31%(6 channels); 74.31%(16 channels) | | Ref.[57], 2019 | Speech imagery | Mean of HbO | RLDA | 3 | 64.1% | | Ref.[102], 2019 | Drowsy and alert states of driving a car simulator | Automatically extracted from different channels and time windows | DNN and CNN | 2 | DNN: 97.2%(the best); CNN: 99.3% | | Ref.[60], 2020 | MI, word generation, n-back and discrimination/selection response task | Automatically extracted from EEG, HbO, HbR, and HbD | DNN and SVM | 2 and 4 | MI task:91%(DNN), 85%(SVM); n-back task: 87%(DNN), 82%(SVM) | | Ref.[103], 2020 | Emotional task | Average level of HbO and HbR | LDA | 2 | 64.50%, 67.75%, 71.00% | | Ref.[92], 2020 | Self-paced walking | TKE and AUC of HbO, HbR, and HbT | GBDT, RF, LR, and LDA | 2 | AUC:94.4%, 93.6%, 82.6%, and 81.9%; TKE(GBDT): 98.75%(offline), 100%(pseudo-online) | | Ref.[104], 2020 | MI of left and right hand, MA and rest | Mean, slope, peak, skewness, and kurtosis of HbO and HbR | LDA, KNN, and SVM | 2 | LDA: 87.87%; KNN: 79.59%; SVM: 89.54%(the best) |
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