TY -非盟的密封·AU - Reddy Puthi Prem Nivesh AU - Chaithanya Pingali盟——Meghana Arramada盟——Jahnavi Kamireddy盟——Krejcar Ondrej盟——Hudak拉多万·PY - 2020 DA - 2020/08/03 TI -一个脑电图数据库及其初始基准情感分类性能SP - 8303465六世- 2020 AB -人类情感识别一直是主要的研究领域在过去的几十年由于其引人注目的学术和工业应用。然而,大多数的最先进的方法识别情绪在分析面部图像。情感识别使用脑电图(EEG)信号受关注较少。然而,使用EEG信号的优势是,它可以捕捉真实的情感。然而,很少有脑电图信号的情感计算数据库是公开的。在这项工作中,我们提出一个数据库组成的EEG信号的44个志愿者。23 44是女性。32通道清晰脑电图旅行者传感器是用来记录四个情绪状态即快乐,恐惧,悲伤,和中性的主题通过显示12个视频。3视频文件是用于每个情感。参与者被映射的情感,他们觉得每个视频看完。 The recorded EEG signals are considered further to classify four types of emotions based on discrete wavelet transform and extreme learning machine (ELM) for reporting the initial benchmark classification performance. The ELM algorithm is used for channel selection followed by subband selection. The proposed method performs the best when features are captured from the gamma subband of the FP1-F7 channel with 94.72% accuracy. The presented database would be available to the researchers for affective recognition applications. SN - 1748-670X UR - https://doi.org/10.1155/2020/8303465 DO - 10.1155/2020/8303465 JF - Computational and Mathematical Methods in Medicine PB - Hindawi KW - ER -