Abstract
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.
Highlights
Human emotional experience plays a central part in our daily lives, our scientific knowledge relating to the human emotions is still very limited. e progress for affective sciences is crucial for the development of human psychology for the benefit and application of the society
Self-Assessment Manikin (SAM) is not feasible to be conducted on young children or elders due to the limitation of literacy skills [4]. erefore, the physiological signals that are transported throughout the human body can provide health information directly from patients to medical professionals and evaluate their conditions almost immediately. e brainwave signal of a human being produces insurmountable levels of neuron signals that manage all functionalities of the body. e human brain stores the emotional experiences that are gathered throughout their lifetime
From the 30 papers identified, only 26 of the papers have reported the number of participants used for emotion classification analysis as summarized in Table 7, and the table is arranged from the highest total number of participants to the lowest. e number of participants varies between the ranges from 5 to 100 participants, and 23 reports stated their gender population with the number of males (408) being higher than females (342) overall, while another 3 reports only stated the number of participants without stating the gender population. 7.70% was reported using less than 10 subjects, 46.15% reported using between 10 and 30 participants, and 46.15% reported using more than 30 participants
Summary
Human emotional experience plays a central part in our daily lives, our scientific knowledge relating to the human emotions is still very limited. e progress for affective sciences is crucial for the development of human psychology for the benefit and application of the society. Is method provides an alternative to the sometimes more difficult assessment of psychological evaluations of a patient done by a medical profession where they would require thorough training and experience to understand the patient’s mental health conditions. Erefore, the physiological signals that are transported throughout the human body can provide health information directly from patients to medical professionals and evaluate their conditions almost immediately. By tapping directly into the brainwave signals, we can examine the emotional responses of a person when exposed to certain environments. With this information provided from the brainwave signals, it can help strengthen and justify the person is physically fit or may be suffering from mental illness
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