Human emotion recognition from EEG-based brain–computer interface using machine learning: a comprehensive review
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Abstract
Abstract Affective computing, a subcategory of artificial intelligence, detects, processes, interprets, and mimics human emotions. Thanks to the continued advancement of portable non-invasive human sensor technologies, like brain–computer interfaces (BCI), emotion recognition has piqued the interest of academics from a variety of domains. Facial expressions, speech, behavior (gesture/posture), and physiological signals can all be used to identify human emotions. However, the first three may be ineffectual because people may hide their true emotions consciously or unconsciously (so-called social masking). Physiological signals can provide more accurate and objective emotion recognition. Electroencephalogram…
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Topics
Keywords
- Computer science
- Electroencephalography
- Artificial intelligence
- Support vector machine
- Brain–computer interface
- Emotion classification
- Affective computing
- Convolutional neural network
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