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Electronic skin (e-skin) is a flexible substrate with integrated electronics that mimics and surpasses the functions of human skin. It is used for continuous and non-invasive recording of biosignals directly from the human body. Typically produced in the form of smart bands, bracelets, patches (such as e-tattoos), rings, textile products, footwear, and more. Artificial Intelligence (AI) significantly accelerates the collection and analysis of data, contributing to better and faster diagnosis of various health disorders.
Findings of researchers from the California Institute of Technology were recently published in a review article in the journal Nature Medicine Intelligence.
Artificial Intelligence in the Design of Electronic Skin
Due to their biocompatibility and cost-effectiveness, natural materials, including cotton and silk, are common substrates for e-skin design. However, the lack of stretchability and regulatory capabilities are significant drawbacks of these materials. Synthesized soft materials have shown promising results in accurately collecting signals. However, these materials require additional testing for biocompatibility and safety.
Machine Learning with AI can identify promising materials with the necessary properties and optimize the synthesis of materials. Additionally, machine learning can be used for quality control during mass production and for optimizing the design of electronic skin.
AI-powered E-Skin for Diagnosis and Treatment
Modern diagnostics is inconceivable without medical technologies based on artificial intelligence. AI-powered e-skin can be used to monitor various biological parameters. Additionally, machine learning algorithms enhance data analysis and prediction.
AI enables the rapid detection of subtle and gradual cardiovascular changes automatically. The technology can also be employed to monitor real-time stress hormone levels for predicting mental health issues. Monitoring medications and metabolism through electronic skin takes personalized therapy to a new level.
Challenges Facing Developers
Data accessibility and security are major concerns associated with the clinical application of AI-powered e-skin. According to researchers, stringent rules are necessary for integrating AI-based models into medical practice, as they can make mistakes. Therefore, it is crucial to ensure that people can trust the predictions generated by AI.
