{"id":200902,"date":"2025-07-21T18:21:25","date_gmt":"2025-07-21T09:21:25","guid":{"rendered":"http:\/\/ee.presscat.kr\/?post_type=research-achieve&p=200902"},"modified":"2026-04-13T02:04:57","modified_gmt":"2026-04-12T17:04:57","slug":"professor-shinhyun-chois-team-develops-next-generation-neuromorphic-semiconductor-based-artificial-sensory-nervous-system","status":"publish","type":"research-achieve","link":"http:\/\/ee.presscat.kr\/en\/research-achieve\/professor-shinhyun-chois-team-develops-next-generation-neuromorphic-semiconductor-based-artificial-sensory-nervous-system\/","title":{"rendered":"Professor Shinhyun Choi\u2019s Team Develops Next-Generation Neuromorphic Semiconductor Based Artificial Sensory Nervous System"},"content":{"rendered":"
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< (Left to right) See\u2011On Park, MS-PhD Integrated student, KAIST School of Electrical Engineering; Jongwon Lee, Professor, Department of Semiconductor Convergence, Chungnam National University; Shinhyun Choi, Professor, School of Electrical Engineering, KAIST ><\/span><\/figcaption><\/figure>\n

With the joint advancement of artificial intelligence and robotics technologies, enabling robots to perceive and respond to their environments as efficiently as humans has become a critical challenge. Recently, a Korean research team has attracted attention by newly implementing an artificial sensory nervous system that mimics biological sensory nerves without any complex software or circuitry. This technology minimizes energy consumption while intelligently reacting to external stimuli, promising applications in ultra\u2011miniature robots, prosthetic hands, and robotics for medical or extreme environments.<\/span><\/p>\n

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A joint research team led by Shinhyun Choi, KAIST Endowed Chair Professor, and Jongwon Lee, Professor in the Department of Semiconductor Convergence at Chungnam National University, together with See\u2011On Park of the integrated MS-PhD program in the KAIST School of Electrical Engineering, has developed a next\u2011generation, neuromorphic\u2011semiconductor\u2011based artificial sensory nervous system. They experimentally demonstrated a novel robotic system that responds efficiently to external stimuli.<\/span><\/p>\n

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Animals, including humans, ignore safe or familiar stimuli but respond selectively and sensitively to important ones, thus preventing energy waste while focusing on crucial signals for swift reaction to environmental changes. For example, one soon tunes out the hum of an air conditioner or the feeling of clothes on the skin, yet quickly focuses on hearing one\u2019s name called or sensing a sharp object touching the skin. This is regulated by the sensory nervous system\u2019s functions of \u201chabituation\u201d and \u201csensitization,\u201d and many have sought to apply these biological features to robots for more efficient, human\u2011like environmental responses.<\/span><\/p>\n

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However, implementing complex features such as habituation and sensitization in robots has required separate software or intricate circuitry, hindering miniaturization and energy efficiency. In particular, efforts using memristors, neuromorphic semiconductor elements whose resistance depends on the history of current flow, have been limited by conventional memristors\u2019 simple conductance changes, which failed to replicate the sensory system\u2019s complexity.<\/span><\/p>\n

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To overcome these limitations, the team engineered a new memristor in which opposing conductance\u2011changing layers coexist within a single device. This structure enables the realistic emulation of habituation and sensitization, as seen in biological sensory nerves.<\/span><\/p>\n

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< Figure 1. Physical appearance and schematic of the new memristor capable of mimicking habituation and sensitization in sensory nerves (top), and comparison of the simple conductance\u2011change behavior of conventional memristors versus the complex conductance patterns of the developed device (bottom). ><\/span><\/figcaption><\/figure>\n

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This device gradually reduces its response upon repeated stimuli and, when a danger signal is detected, becomes sensitized again, faithfully reproducing the complex synaptic response patterns of real nervous systems.<\/span><\/p>\n

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Using these memristors, the researchers built a memristor\u2011based artificial sensory nervous system for touch and pain detection, and attached it to a robotic hand to test its efficiency. When safe tactile stimuli were repeatedly applied, the robotic hand initially sensitive to the novel touch began to ignore it, demonstrating habituation. Later, when an electric shock accompanied the touch (a danger signal), the system recognized it as such and regained sensitivity, confirming the sensitization function.<\/span><\/p>\n

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< Figure 2. Experimental results of the robotic hand equipped with the memristor\u2011based artificial sensory nervous system. By ignoring unimportant stimuli, the system improves energy efficiency and reduces processor load. ><\/span><\/figcaption><\/figure>\n

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These experiments prove that robots can respond to stimuli as efficiently as humans without complex software or processors, validating the feasibility of energy\u2011efficient, neuro\u2011inspired robots.<\/span><\/p>\n

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See\u2011On Park, first author of the study, stated, \u201cBy emulating the human sensory nervous system with next\u2011generation semiconductors, we\u2019ve opened the door to a new class of robots that respond more intelligently and with greater energy efficiency to their environments. We expect applications in ultra\u2011miniature robots, military robots, and medical prostheses, where the convergence of advanced semiconductors and robotics is critical.\u201d<\/span><\/p>\n

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This research was published online on July\u00a01, 2025, in the international journal Nature Communications.<\/span><\/p>\n

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Paper title: Experimental demonstration of third\u2011order memristor\u2011based artificial sensory nervous system for neuro\u2011inspired robotics<\/span><\/p>\n

DOI:\u00a0https:\/\/doi.org\/10.1038\/s41467-025-60818-x<\/a><\/span><\/p>\n

This research was supported by the National Research Foundation of Korea\u2019s Next\u2011Generation Intelligent Semiconductor Technology Development Project, Mid\u2011Career Research Program, PIM AI Semiconductor Core Technology Development Project, Outstanding Young Researcher Program, and the Nano Comprehensive Technology Institute\u2019s Nanomedical Devices Project.<\/span><\/p>\n

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