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Emotion recognition is a prominent research subject in the fields of affective computing and human-computer interaction. To address the emotion recognition problem, input signals can be categorized into 4 types. The physiological signals are considered more reliable than facial, gesture, and speech signals because they are less susceptible to subjective control by individuals. Additionally, using speech signals is often ineffective in noisy environments, and language barriers further limit its practicality. Also, camera-based methods raise significant security concerns, particularly in systems that involve continuous indoor monitoring, where there is a high risk of privacy violations. Furthermore, video data demands more storage and processing resources compared to physiological signals. Therefore, physiological data not only provides a more objective and consistent basis for emotion recognition but is also more secure and efficient to handle.
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IEEE/ICACT20250190 Slide.02
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