神经形态工程学
材料科学
纳米技术
电子材料
电子皮肤
计算机科学
人工智能
人工神经网络
作者
Chandrashekhar S. Patil,Sourabh B. Ghode,Jungmin Kim,Girish U. Kamble,Somnath S. Kundale,Abdul Mannan,Youngbin Ko,Muhammad Noman,Qazi Muhammad Saqib,Swapnil R. Patil,Sangrak Bae,Jin Hyeok Kim,Jun Hong Park,Jinho Bae
摘要
Neuromorphic devices represent an important advancement in technology, drawing inspiration from the intricate and efficient mechanisms of the human brain. This review paper elucidates the diverse landscape of neuromorphic electronic skin (e-skin) technologies while highlighting their numerous applications. Here, neuromorphic devices for e-skin are classified as two types of direct neuromorphic e-skins combining both neuromorphic devices and sensors, and indirect e-skins separating neuromorphic devices and sensors. In direct neuromorphic e-skins, there are developing devices like memristor-based neuromorphic devices with sensors and transistor-based neuromorphic devices with sensors. On the other hand, indirect types are demonstrated as separated neuromorphic and sensor parts systems through the various interfacing structures. It also describes recent neuromorphic developments in artificial neural networks (ANNs), deep neural networks (DNNs), and convolutional neural networks (CNNs), for the real-time interpretation of sensory data. Moreover, it introduces multimodal sensory feedback, soft and flexible e-skins, and more intuitive human-machine interfaces. This review examines various applications, including smart textiles for the development of next-generation wearable bioelectronics, brain-sensing interfaces that enhance tactile perception, and the integration of human-machine interfaces aimed at replicating the biological sensorimotor loop, which can improve health monitoring and biomedical applications. Additionally, the review also highlights the potential of neuromorphic e-skin in human-robot interaction, particularly in the context of continuous prosthetic control and robotics. Through this analysis, the paper provides insights into current advancements, identifies key challenges, and suggests future research directions for optimizing neuromorphic e-skin devices and expanding their practical implementation.
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