In a cutting-edge breakthrough, researchers at UNIST have developed a technology for real-time human emotion recognition. This groundbreaking innovation has the potential to transform various industries by focusing on wearable systems. The team successfully tackled the challenge of interpreting abstract emotional data by creating a multi-modal system that combines verbal and non-verbal expression data.
The system utilizes a personalized skin-integrated facial interface (PSiFI) powered by friction charging, incorporating a bidirectional triboelectric strain and vibration sensor for simultaneous data sensing and integration. This fully integrated data processing circuit ensures wireless real-time emotion recognition, even when individuals are wearing masks.
Impressive accuracy has been demonstrated through the use of machine learning algorithms in identifying human emotions, as shown in a digital concierge application within virtual reality (VR) environments. By incorporating information from facial muscle deformation and vocal cord vibrations, the system offers personalized services based on users’ emotions.
This advancement in human-machine interface (HMI) devices opens up possibilities for portable emotion recognition devices and next-generation digital platform services. Collaboration with Nanyang Technical University in Singapore, supported by the National Research Foundation of Korea (NRF) and the Korea Institute of Materials (KIMS), underscores the importance of this innovation in enhancing interaction capabilities between humans and machines.
UNIST researchers have created a cutting-edge technology that can recognize human emotions in real-time using wearable systems. The team addressed the challenge of interpreting abstract emotional data by developing a multi-modal system that combines verbal and non-verbal expression data.
The system utilizes a personalized skin-integrated facial interface (PSiFI) powered by friction charging, incorporating a bidirectional triboelectric strain and vibration sensor for simultaneous data sensing and integration. The fully integrated data processing circuit ensures wireless real-time emotion recognition, even when individuals are wearing masks.
Impressive accuracy has been demonstrated through the use of machine learning algorithms in identifying human emotions, as shown in a digital concierge application within virtual reality (VR) environments. By incorporating information from facial muscle deformation and vocal cord vibrations, the system offers personalized services based on users’ emotions.
This advancement in human-machine interface (HMI) devices opens up possibilities for portable emotion recognition devices and next-generation digital platform services. Collaboration with Nanyang Technical University in Singapore, supported by the National Research Foundation of Korea (NRF) and the Korea Institute of Materials (KIMS), underscores the importance of this innovation in enhancing interaction capabilities between humans and machines.
In summary, UNIST researchers have developed an innovative technology that can recognize human emotions in real-time using wearable systems. The multi-modal system combines verbal and non