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迈向人工智能时代：电子皮肤的进展。

Toward an AI Era: Advances in Electronic Skins.

机构信息

Department of Materials Science and Engineering, National University of Singapore, Singapore 117575, Singapore.

Institute for Health Innovation & Technology, National University of Singapore, Singapore 119276, Singapore.

出版信息

Chem Rev. 2024 Sep 11;124(17):9899-9948. doi: 10.1021/acs.chemrev.4c00049. Epub 2024 Aug 28.

DOI:10.1021/acs.chemrev.4c00049
PMID:39198214
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11397144/
Abstract

Electronic skins (e-skins) have seen intense research and rapid development in the past two decades. To mimic the capabilities of human skin, a multitude of flexible/stretchable sensors that detect physiological and environmental signals have been designed and integrated into functional systems. Recently, researchers have increasingly deployed machine learning and other artificial intelligence (AI) technologies to mimic the human neural system for the processing and analysis of sensory data collected by e-skins. Integrating AI has the potential to enable advanced applications in robotics, healthcare, and human-machine interfaces but also presents challenges such as data diversity and AI model robustness. In this review, we first summarize the functions and features of e-skins, followed by feature extraction of sensory data and different AI models. Next, we discuss the utilization of AI in the design of e-skin sensors and address the key topic of AI implementation in data processing and analysis of e-skins to accomplish a range of different tasks. Subsequently, we explore hardware-layer in-skin intelligence before concluding with an analysis of the challenges and opportunities in the various aspects of AI-enabled e-skins.

摘要

电子皮肤（e-skins）在过去二十年中受到了广泛关注并得到了快速发展。为了模仿人类皮肤的功能，设计并集成了多种用于检测生理和环境信号的柔性/可拉伸传感器到功能系统中。最近，研究人员越来越多地部署机器学习和其他人工智能（AI）技术来模仿人类神经系统，以处理和分析 e-skins 收集的感觉数据。人工智能的集成具有在机器人技术、医疗保健和人机接口中实现高级应用的潜力，但也存在数据多样性和 AI 模型鲁棒性等挑战。在这篇综述中，我们首先总结了 e-skins 的功能和特点，然后介绍了感觉数据的特征提取和不同的 AI 模型。接下来，我们讨论了 AI 在 e-skin 传感器设计中的应用，并解决了 AI 在 e-skin 数据处理和分析中实现的关键问题，以完成各种不同的任务。随后，我们探讨了硬件层的皮肤内智能，最后分析了 AI 赋能的 e-skins 在各个方面所面临的挑战和机遇。

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