Systematic Literature Review: On Measuring the Level of Emotional Experience Based on EEG Signals

This research aims to produce a literature review using a structured approach, Systematic Literature Review (SLR), so that readers can easily understand the aim and objectives of this research article. Furthermore, this study aims to identify “what methodologies are available to measure emotional experi- ences via EEG signals.” It can also indicate research gaps that can be used to develop research questions. The article search and selection approach follows the PRISMA guidelines., considering established criteria. This research was conducted through a systematic literature review focusing on essential factors for measuring emotional experience. The process is divided into several steps: selecting online database sources for research literature, reviewing research objectives and questions, creating a search strategy, setting search criteria, defining inclusion and exclusion criteria, and extracting data; the results are then examined and analysed to address the research inquiries. We can conduct further research by looking at the resulting mapping references; for this research, we opted to utilize the dataset SEED and GNN algorithm. The research we will carry out is to detect individual emotional and mental levels using the SEED dataset and using the Graph Neural Network (GNN) algorithm. Measuring the intensity of emotional experience is a popular research area; many have carried out such research with various algorithms and datasets generated from EEG signals.