Specialists at the University of Science and Technology Unist have recently unveiled groundbreaking technology capable of recognizing human emotions in real time. This development is expected to bring significant changes to various industries, particularly the next generation wearable devices sector which will offer services tailored to users’ emotions.
Accurately extracting emotional information has long been a challenge due to the subjective and complex nature of human reactions like emotions, moods, and feelings. The new multimodal system for recognizing human emotions combines both verbal and non-verbal expressions data, enabling more comprehensive emotional analysis.
The core of the system is the PSIFI interface (Personalized Skin-Integrated Facial Interface), which is self-contained, user-friendly, stretchable, and transparent. Equipped with a unique sensor that can detect deformations and vibrations, the system seamlessly integrates verbal and non-verbal data for instant emotion recognition.
Utilizing machine learning algorithms, this technology can accurately identify human emotions in real time even when a person’s face is covered. By detecting facial muscle movements and vocal cord vibrations, the system ensures precise emotion recognition.
Operating on the principle of “charging by friction” (triboelectric effect), the system is self-powered and does not rely on external power sources or complex equipment for data processing.
Developers highlight the system’s ability to be personalized for each user, achieved through semi-drying technology for creating transparent charging electrodes and multi-point molding for flexible and transparent personalized masks.
The technology has already been implemented in virtual reality applications for digital concierge services in smart homes, private cinemas, and offices. Its capacity to identify individual emotions in varied scenarios enables tailored recommendations for music, movies, and books.
In experiments testing the system’s efficiency in real-time emotion recognition, researchers gathered multidimensional data on facial muscle deformations and vocal cord vibrations. This innovative approach not only enhances the understanding of human emotions but also paves the way for personalized technologies and services grounded in emotional interactions.