Review Article
A Review of Hybrid Brain-Computer Interface Systems
Table 1
A comparison of several different BCI hybrid systems.
| Paper # | Hybrid type | System organization | Improvement | Number of subjects | Classification |
| [15] | ERD, SSVEP | Simultaneous | Accuracy significantly improved compared to ERD and slightly better than SSVEP | 14 | LDA | [16] | ERD, SSVEP | Sequential | False positive rate was reduced | 6 | FLDA | [27] | ERD, SSVEP | Sequential | Application of BCI for FES triggering was improved | 3 | Filters and thresholds | [28] | ERD, SSVEP | Simultaneous | Feedbacks were added to the work done in [15] | 12 | LDA | [29] | P300, SSVEP | Sequential | Improved ITR | 10 | FLDA and BLDA | [30] | P300, SSVEP | Sequential | New application (smart home) | 3 | LDA | [31] | P300, ERD | Sequential | Improvement in application (wheelchair control) | 2 | Frequency analysis | [32] | P300, ERD | Sequential | Expand control functions in virtual environment | 4 | SVM and FLDA | [33] | P300, ERD | Simultaneous | Increase reliability | 4 | Fisher’s discriminant analysis | [34] | ERD, NIRS | Simultaneous | Improvement in classification accuracy and performance | 14 | LDA | [35] | EEG, EMG | Simultaneous | Improvement in performance | 12 | Frequency analysis and Gaussian classifier | [36] | ERD, EOG | Simultaneous | Improvement in classification accuracy, reduction in number of electrodes and training time | 3 | Frequency analysis | [37] | ERD, EOG | Sequential | Improvement in performance | 7 | LDA |
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