A research team led by Professor Hyeok Kim at the University of Seoul has developed an electronic skin capable of rapidly self-healing from external damage. The study was published in Science Advances on February 12, 2025.

 To address durability challenges, the team introduced disulfide bonds into thermoplastic polyurethane (TPU) and incorporated isophorone diisocyanate (IPDI) to maximize self-healing performance. As a result, the electronic skin achieved an 80% recovery rate within just 10 seconds at room temperature, significantly enhancing device durability and the reliability of biometric signal measurements.

 The electronic skin successfully measured various signals, including motion, electromyography (EMG), and electrocardiography (ECG). Notably, EMG data were integrated with a deep learning-based model to enable real-time muscle fatigue monitoring, achieving an accuracy rate of over 95%.

 Professor Kim stated, "This study significantly improves the durability and functionality of electronic skin. By integrating deep learning-based real-time biometric signal analysis, we have enhanced the commercialization potential of wearable medical devices."

Schematic representation of the self-healing mechanism of the E-Skin

[Reference] Kim, Hyeok, et al. "Rapidly self-healing electronic skin for machine learning–assisted physiological and movement evaluation." Science Advances 11.7 (2025): eads1301.

[Main Author] Yongju Lee(University of Seoul), Hyeok Kim(University of Seoul) * Contact email : prof. Hyeok Kim : hyoek.kim@uos.ac.kr