Table 4.
Neurosky MindWave Studies.
| Paper | Year | Features | Classification | Accuracy | Size |
|---|---|---|---|---|---|
| Jones and Schwartz | 2010 | Spectral Features | N/A | N/A | 5 |
| AlZu'bi et al. | 2013 | PSD, log variance, stats | Fatigue index | N/A | 1 |
| Shin et al. | 2013 | Spectral Features | SVM | 88.90% | 1 |
| Lim et al. | 2014 | Alpha band power | Triggering window | 31% | 50 |
| Suprihadi and Karyono | 2014 | Spectral Features | Spectral threshold | 68.11% | 1 |
| Abdel-Rahman et al. | 2015 | Periodogram | Neural network | 97.60% | 60 |
| Dunne et al. | 2015 | Alpha and Beta Features | Threshold | 81% | 3 |
| Joshi et al. | 2015 | Spectral Features | Threshold | N/A | 1 |
| Lin et al. | 2015 | Spectral Features | Threshold | N/A | 1 |
| Putra et al. | 2016 | Spectral Features | Threshold | N/A | 0 |
| Sadeghi et al. | 2016 | Alpha, Beta, Theta Power | Markov Chain Model | 91% | 1 |
| Patel et al. | 2017 | Spectral Features | Paired t-test | N/A | 7 |
| Anwar et al. | 2018 | Spectral Features | Averaged threshold | 75% | 20 |
| Sethi et al. | 2018 | Spectral Features, eSense | N/A | N/A | 42 |
| Aboalayon and Faezipour | 2019 | Spectral Features | N/A | N/A | 1 |
| Nissimagoudar and Nandi | 2020 | Spectral Features | SVM | 74-89% | 10 |