Faculty of Computing & Informatics, Universiti Malaysia Sabah, Jalan UMS, Kota Kinabalu 88400, Sabah, Malaysia.
Comput Intell Neurosci. 2020 Sep 16;2020:8875426. doi: 10.1155/2020/8875426. eCollection 2020.
Emotions are fundamental for human beings and play an important role in human cognition. Emotion is commonly associated with logical decision making, perception, human interaction, and to a certain extent, human intelligence itself. With the growing interest of the research community towards establishing some meaningful "emotional" interactions between humans and computers, the need for reliable and deployable solutions for the identification of human emotional states is required. Recent developments in using electroencephalography (EEG) for emotion recognition have garnered strong interest from the research community as the latest developments in consumer-grade wearable EEG solutions can provide a cheap, portable, and simple solution for identifying emotions. Since the last comprehensive review was conducted back from the years 2009 to 2016, this paper will update on the current progress of emotion recognition using EEG signals from 2016 to 2019. The focus on this state-of-the-art review focuses on the elements of emotion stimuli type and presentation approach, study size, EEG hardware, machine learning classifiers, and classification approach. From this state-of-the-art review, we suggest several future research opportunities including proposing a different approach in presenting the stimuli in the form of virtual reality (VR). To this end, an additional section devoted specifically to reviewing only VR studies within this research domain is presented as the motivation for this proposed new approach using VR as the stimuli presentation device. This review paper is intended to be useful for the research community working on emotion recognition using EEG signals as well as for those who are venturing into this field of research.
情绪是人类的基本特征，在人类认知中起着重要作用。情绪通常与逻辑决策、感知、人际互动以及在某种程度上与人类自身的智力有关。随着研究界对建立人类与计算机之间有意义的“情感”交互的兴趣日益浓厚，人们需要可靠的、可部署的解决方案来识别人类的情绪状态。最近使用脑电图 (EEG) 进行情绪识别的发展引起了研究界的浓厚兴趣，因为最新的消费级可穿戴 EEG 解决方案可以提供一种廉价、便携和简单的识别情绪的方法。由于上次全面审查是在 2009 年至 2016 年期间进行的，因此本文将更新 2016 年至 2019 年期间使用 EEG 信号进行情绪识别的最新进展。本次最新研究综述的重点是情绪刺激类型和呈现方式、研究规模、EEG 硬件、机器学习分类器和分类方法等要素。从这项最新研究综述中，我们提出了一些未来的研究机会，包括提出一种以虚拟现实 (VR) 的形式呈现刺激的不同方法。为此，专门在本节中介绍了一个专门用于审查该研究领域内仅 VR 研究的部分，作为使用 VR 作为刺激呈现设备的新方法的动机。本文旨在为使用 EEG 信号进行情绪识别的研究人员以及涉足该研究领域的人员提供有用的参考。
