Rapidly self-healing electronic skin for machine learning–assisted physiological and movement evaluation

Emerging electronic skins (E-Skins) offer continuous, real-time electrophysiological monitoring. However, daily mechanical scratches compromise their functionality, underscoring urgent need for self-healing E-Skins resistant to mechanical damage. Current materials have slow recovery times, impeding reliable signal measurement. The inability to heal within 1 minute is a major barrier to commercialization. A composition achieving 80% recovery within 1 minute has not yet been reported. Here, we present a rapidly self-healing E-Skin tailored for real-time monitoring of physical and physiological bioinformation. The E-Skin recovers more than 80% of its functionality within 10 seconds after physical damage, without the need of external stimuli. It consistently maintains reliable biometric assessment, even in extreme environments such as underwater or at various temperatures. Demonstrating its potential for efficient health assessment, the E-Skin achieves an accuracy exceeding 95%, excelling in wearable muscle strength analytics and on-site AI-driven fatigue identification. This study accelerates the advancement of E-Skin through rapid self-healing capabilities.

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Publication Details

Journal
Science Advances
Published
2025-02-12
DOI
https://doi.org/10.1126/sciadv.ads1301
Citations
30
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
20.22

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article

Rapidly self-healing electronic skin for machine learning–assisted physiological and movement evaluation

Dong‐Wook Park, Tae‐Woo Lee, Tanveer A. Tabish, Ali Khademhosseini et al.
30 citations
Science Advances
Advanced Sensor and Energy Harvesting Materials
20.22
article

Rapidly self-healing electronic skin for machine learning–assisted physiological and movement evaluation

Dong‐Wook Park, Tae‐Woo Lee, Tanveer A. Tabish, Ali Khademhosseini, Hyo-Jeong Choi, Sam Emaminejad, Zhuohong Wu, Ju-Hwan Kim, Xuanbing Cheng, Keren Zhou, Xinyu Tian, Yangzhi Zhu, Sang Won Lee, Hyeok Kim, Yongju Lee, Jae-Won Park, Dong Hyun Nam
article en
30 citations

Abstract

Emerging electronic skins (E-Skins) offer continuous, real-time electrophysiological monitoring. However, daily mechanical scratches compromise their functionality, underscoring urgent need for self-healing E-Skins resistant to mechanical damage. Current materials have slow recovery times, impeding reliable signal measurement. The inability to heal within 1 minute is a major barrier to commercialization. A composition achieving 80% recovery within 1 minute has not yet been reported. Here, we present a rapidly self-healing E-Skin tailored for real-time monitoring of physical and physiological bioinformation. The E-Skin recovers more than 80% of its functionality within 10 seconds after physical damage, without the need of external stimuli. It consistently maintains reliable biometric assessment, even in extreme environments such as underwater or at various temperatures. Demonstrating its potential for efficient health assessment, the E-Skin achieves an accuracy exceeding 95%, excelling in wearable muscle strength analytics and on-site AI-driven fatigue identification. This study accelerates the advancement of E-Skin through rapid self-healing capabilities.

Science AdvancesVol. 11(7)
University of Seoul (KR), Seoul National University (KR), University of California, Los Angeles (US), British Heart Foundation (GB), University of California San Diego (US), Terasaki Foundation (US)
National Research Foundation, National Research Foundation of Korea, National Institutes of Health
Life below water
Openalex Percentile: Top 0%
Advanced Sensor and Energy Harvesting Materials
20.22
DOIOpen Access PDFOpenAlex
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