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Mini review: Challenges in EEG emotion recognition

Profile image of Josep M. Fort MirJosep M. Fort Mir

2024, Frontiers in Psychology

https://doi.org/10.3389/FPSYG.2023.1289816
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Abstract

Electroencephalography (EEG) stands as a pioneering tool at the intersection of neuroscience and technology, o ering unprecedented insights into human emotions. Through this comprehensive review, we explore the challenges and opportunities associated with EEG-based emotion recognition. While recent literature suggests promising high accuracy rates, these claims necessitate critical scrutiny for their authenticity and applicability. The article highlights the significant challenges in generalizing findings from a multitude of EEG devices and data sources, as well as the di culties in data collection. Furthermore, the disparity between controlled laboratory settings and genuine emotional experiences presents a paradox within the paradigm of emotion research. We advocate for a balanced approach, emphasizing the importance of critical evaluation, methodological standardization, and acknowledging the dynamism of emotions for a more holistic understanding of the human emotional landscape.

FAQs

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What explains the discrepancy in EEG accuracy rates under subject-dependent conditions?add

Research indicates that subject-dependent models achieve accuracy rates as high as 96.89%, compared to lower rates of 74.52% under subject-independent conditions, indicating overfitting to individual data.

How significant is the role of data standardization in EEG emotion research?add

The lack of standardization across EEG devices complicates reproducibility, as architectures vary significantly from low-density to high-density systems, which impacts the generalizability of findings.

When did the field start observing inflated accuracy claims in EEG studies?add

Inflated accuracy claims in EEG emotion recognition have been noted in studies since at least 2022, particularly due to simplified emotional models that do not reflect real-world complexity.

Why do current EEG methodologies struggle with capturing true emotional experiences?add

Current methodologies struggle due to the rigid nature of laboratory settings, which often do not emulate the fluid and dynamic nature of real-life emotional experiences.

What limitations do researchers face when collecting EEG data in practical scenarios?add

Researchers face significant limitations such as the need for specialized expertise and standardized equipment, which often restricts the applicability and generalization of EEG-based emotion recognition.

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