Table 1.
Comparison of the specific characteristics of The Studies in the field of HBCI
| Paper | Combined Control Signals | Combination Type | Classification | Application | Result |
|---|---|---|---|---|---|
| Yin et al. (2014) | P300+SSVEP | Sequential | FLDA, BLDA | Object control | Fast and accurate detection of the control state of subject |
| Wang et al. (2015) | P300+SSVEP | Sequential | SWLDA | Speller | Increase the classification accuracy |
| Bharne et al. (2015) | P300+SSVEP | Simultaneous | SWLDA | Speller | Reduce errors+increase the classification accuracy and ITR |
| Panicker et al. (2011) | P300+SSVEP | Simultaneous | SWLDA, CCA | Speller | Increase the classification speed |
| Edlinger et al. (2011) | P300+SSVEP | Simultaneous | BLDA, CCA | Target selection | Increase the classification speed |
| Yin et al. (2013) | P300+SSVEP | Sequential | LDA | Object control | Increase the classification speed |
| Xu et al. (2013) | P300+SSVEP | Simultaneous | SVM-FLDA | Curser movement | Inappropriate speed and ignoring the control state of subject due to system synchronization |
| Xu et al. (2013) | P300+SSVEP | Sequential | Kernel FDA, SVM | Object control | Increase the classification accuracy |
| Xu et al. (2013) | P300+SSVEP | Sequential | SVM | Object control | Increase the classification accuracy |
| Xu et al. (2013) | P300+SSVEP | Simultaneous | LDA, SWLDA | Speller | Increase the classification accuracy and ITR |
| Xu et al. (2013) | P300+SSVEP | Sequential | SVM, LDA | Speller | Increase the ITR |
| Allison et al. (2010) | SSVEP+ERD | Simultaneous | FLDA | Curser movement | Increase the classification accuracy |
| Savić et al. (2011) | SSVEP+ERD | Sequential | LDA | Orthotics control | Decrease the positive error rate |
| Brunner et al. (2011) | SSVEP+ERD | Simultaneous | LDA | Curser movement | Increase the classification accuracy and ITR |
| Pfurtscheller et al. (2010) | SSVEP+ERD | Sequential | - | Neural prosthesis control | Reduce the time spent |
| Allison et al. (2012) | SSVEP+ERD | Simultaneous | LDA | Curser movement | Continuous and simultaneous movement in two dimensions |
| Li et al. (2013) | SSVEP+ERD | Simultaneous | LDA | Wheelchair control | Simultaneous control of direction and speed |
| Li et al. (2014) | SSVEP+ERD | Simultaneous | SVM | Wheelchair control | Simultaneous set of direction and speed with spend the least possible time and high classification accuracy |
| Cao et al. (2014) | SSVEP+ERD | Simultaneous | RBF-SVM | Wheelchair control | Realization of eight control command |
| Cao et al. (2014) | SSVEP+ERD | Simultaneous | SVM | Object control | Achieve optimal performance |
| Rebsamen et al. (2008) | P300+ERD | Sequential | - | Wheelchair control | To determine and fulfill the stop command |
| Long et al. (2012a) | P300+ERD | Simultaneous | LDA | Wheelchair control | Direction and speed control |
| Finke et al. (2011) | P300+ERD | Sequential | FDA | Robot control | Providing movement in various dimensions |
| Su et al. (2011) | P300+ERD | Simultaneous | SVM, FLDA | Object control | Realization of more complex tasks |
| Riechmann et al. (2011) | P300+ERD | Sequential | LDA | Robot control | Robot control |
| Riechmann et al. (2011) | P300+ERD | Sequential | LDA | Speller | Increase the classification accuracy and ITR |
| Riechmann et al. (2011) | P300+ERD | Sequential | LDA | Speller | Increase the classification accuracy and ITR |
| Usakli et al. (2009) | EEG+EOG | Sequential | - | Robot control | Affective robot control |
| Riccio et al. (2015) | EEG+EOG | Simultaneous | SVM | Prosthesis control | Increase the classification accuracy |
| Riccio et al. (2015) | EEG+EOG | Simultaneous | - | Vigilance estimation | Improve the performance |
| Kim et al. (2015) | EEG+Eye Tracker | Sequential | SVM | Curser movement | Increase the ITR |
| Kim et al. (2015) | EEG+Eye Tracker | Sequential | LDA | Curser movement | Increase the ITR |
| Lin et al. (2015) | EEG+EMG | Simultaneous | - | Speller | Increase the classification accuracy |
| Leeb et al. (2011) | EEG+EMG | Sequential | - | Speller | Increase the classification accuracy+ITR and the number of target items |
| Riccio et al. (2015) | EEG+EMG | Sequential | - | Speller | Improve the performance and ITR |
| Riccio et al. (2015) | EEG+EMG | Simultaneous | CCA | Speller | Increase the classification accuracy+the number of targets and ITR |
| Riccio et al. (2015) | EEG+EMG | Simultaneous | LDA | Object control | Increase the classification accuracy |
| Riccio et al. (2015) | EEG+EMG | Simultaneous | SVM | Object control | Improve the object control |
| Ahn et al. (2013) | EEG+SSSEP | Sequential/Simultaneous | - | Curser movement | Decrease the classification accuracy in simultaneous combination |
| Yao et al. (2014a) | EEG+SSSEP | Simultaneous | - | Curser movement | Providing multi-class BCI system |
| Yao et al. (2014b) | EEG+SSSEP | Simultaneous | LDA | Object control | Increase the classification accuracy |
| Yao et al. (2014a) | EEG+SSSEP | Simultaneous | LDA | Object control | Achieve optimal subjects’ performance |
| Khan et al. (2014a) | EEG+NIRS | Simultaneous | - | Wheelchair control | Realization a large number of commands |
| Yao et al. (2014b) | EEG+NIRS | Simultaneous | LDA | - | Increase the ITR |
| Yao et al. (2014a) | EEG+NIRS | Simultaneous | LDA | - | Provide open access dataset |
| Al-Shargie et al. (2016) | EEG+NIRS | Simultaneous | SVM | Stress assessment | Increase the classification accuracy and improve sensitivity and specificity |
SSVEP: Steady-State Visual Evoked Potential; ERD: Event-Related Desynchronization; EEG: Electroencephalogram; EOG: Electrooculogram; EMG: Electromyogram; SSSEP: Steady-State Somatosensory Evoked Potentials; NIRS: Near-Infrared Spectroscopy; and ITR: Information Transfer Rate