Bubble

Feeling

Cognitive psychology

Emotion classification

Affective computing

Social psychology

Psychiatry

Parallel computing

Computer science

Maximum bubble pressure method

Affective science

Psychology

Interface (matter)

Emotion recognition

Artificial intelligence

Deep learning

Consistency (knowledge bases)

Human–computer interaction

Neuroimaging

Journal of Applied Science and Technology Trends

New research into human-computer interaction seeks to consider the consumer's emotional status to provide a seamless human-computer interface. This would make it possible for people to survive and be used in widespread fields, including education and medicine. Multiple techniques can be defined through human feelings, including expressions, facial images, physiological signs, and neuroimaging strategies. This paper presents a review of emotional recognition of multimodal signals using deep learning and comparing their applications based on current studies. Multimodal affective computing systems are studied alongside unimodal solutions as they offer higher accuracy of classification. Accuracy varies according to the number of emotions observed, features extracted, classification system and database consistency. Numerous theories on the methodology of emotional detection and recent emotional science address the following topics. This would encourage studies to understand better physiological signals of the current state of the science and its emotional awareness problems.

Multimodal Emotion Recognition using Deep Learning