Research Article
DE-CNN: An Improved Identity Recognition Algorithm Based on the Emotional Electroencephalography
Table 1
Summary of the literature review.
| Papers | EEG content | Method | Time (s) | EER | AAC |
| [14] | Eye blinking and self- or non-self-rapid serial visual presentation | Machine learning | 3 | — | 0.9076 | [15] | Relax and eye-closed | Machine learning | 60 | 0.0073 | 0.9893 | [16] | MI-EEG | 1DCNN-LSTM | 1 | 0.0041 | 0.995 | [17] | Imaginary speech | Deep learning | Four words | — | 0.97 | [18] | Relax and eye-closed | Attention-RNN | 1/128 | — | 0.998 | [9] | Emotion video (different stimulant) | 2DCNN + LSTM | 12 | — | 1 |
|
|