The human brain is a complex organ, still completely undiscovered, that
controls almost all the parts of the body. Apart from survival, the human brain
stimulates emotions. Recent research indicates that brain signals can be very
effective for emotion recognition. However, which parts of the brain exhibit
most of the emotions is still under-explored. In this study, we empirically
analyze the contribution of each part of the brain in exhibiting emotions. We
use the DEAP dataset to find the most optimal electrode set which eventually
leads to the effective brain part associated with emotions. We use Fast Fourier
Transformation for effective feature extraction and a 1D-CNN with residual
connection for classification. Though 32 electrodes from the DEAP dataset got
an accuracy of 97.34%, only 12 electrodes (F7, P8, O1, F8, C4, T7, PO3, Fp1,
Fp2, O2, P3, and Fz) achieve 95.81% accuracy. This study also shows that adding
more than 10 electrodes does not improve performance significantly. Moreover,
the frontal lobe is the most important for recognizing emotion.

人脑是一个复杂的器官，主要控制身体的各个部分，同时也影响情绪。最近的研究表明，脑信号对情绪识别非常有效，但大部分情绪主要集中于哪些脑部尚未被充分探索。本研究通过实证分析了各个脑部在情绪表现中的贡献，并利用 DEAP 数据集找到与情绪相关的最优电极组合。研究采用快速傅里叶变换进行有效特征提取，同时通过带有残差连接的一维卷积神经网络进行分类。实验结果表明，从 DEAP 数据集中的 32 个电极中，只有 12 个电极（F7、P8、O1、F8、C4、T7、PO3、Fp1、Fp2、O2、P3 和 Fz）可以达到 95.81% 的准确率，而添加超过 10 个电极并不能显著提高性能。此外，额叶对情绪识别最为重要。