Bio‐Inspired Neuromorphic Sensory Systems from Intelligent Perception to Nervetronics
Abstract Inspired by the extensive signal processing capabilities of the human nervous system, neuromorphic artificial sensory systems have emerged as a pivotal technology in advancing brain‐like computing for applications in humanoid robotics, prosthetics, and wearable technologies. These systems m...
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| Format: | Article |
| Language: | English |
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Wiley
2025-01-01
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| Series: | Advanced Science |
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| Online Access: | https://doi.org/10.1002/advs.202409568 |
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| author | Elvis K. Boahen Hyukmin Kweon Hayoung Oh Ji Hong Kim Hayoung Lim Do Hwan Kim |
| author_facet | Elvis K. Boahen Hyukmin Kweon Hayoung Oh Ji Hong Kim Hayoung Lim Do Hwan Kim |
| author_sort | Elvis K. Boahen |
| collection | DOAJ |
| description | Abstract Inspired by the extensive signal processing capabilities of the human nervous system, neuromorphic artificial sensory systems have emerged as a pivotal technology in advancing brain‐like computing for applications in humanoid robotics, prosthetics, and wearable technologies. These systems mimic the functionalities of the central and peripheral nervous systems through the integration of sensory synaptic devices and neural network algorithms, enabling external stimuli to be converted into actionable electrical signals. This review delves into the intricate relationship between synaptic device technologies and neural network processing algorithms, highlighting their mutual influence on artificial intelligence capabilities. This study explores the latest advancements in artificial synaptic properties triggered by various stimuli, including optical, auditory, mechanical, and chemical inputs, and their subsequent processing through artificial neural networks for applications in image recognition and multimodal pattern recognition. The discussion extends to the emulation of biological perception via artificial synapses and concludes with future perspectives and challenges in neuromorphic system development, emphasizing the need for a deeper understanding of neural network processing to innovate and refine these complex systems. |
| format | Article |
| id | doaj-art-819b18687fbf463caeb639a33358a8b0 |
| institution | Kabale University |
| issn | 2198-3844 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advanced Science |
| spelling | doaj-art-819b18687fbf463caeb639a33358a8b02025-01-09T11:44:45ZengWileyAdvanced Science2198-38442025-01-01121n/an/a10.1002/advs.202409568Bio‐Inspired Neuromorphic Sensory Systems from Intelligent Perception to NervetronicsElvis K. Boahen0Hyukmin Kweon1Hayoung Oh2Ji Hong Kim3Hayoung Lim4Do Hwan Kim5Department of Chemical Engineering Hanyang University Seoul 04763 Republic of KoreaDepartment of Chemical Engineering Hanyang University Seoul 04763 Republic of KoreaDepartment of Chemical Engineering Hanyang University Seoul 04763 Republic of KoreaDepartment of Chemical Engineering Hanyang University Seoul 04763 Republic of KoreaDepartment of Chemical Engineering Hanyang University Seoul 04763 Republic of KoreaDepartment of Chemical Engineering Hanyang University Seoul 04763 Republic of KoreaAbstract Inspired by the extensive signal processing capabilities of the human nervous system, neuromorphic artificial sensory systems have emerged as a pivotal technology in advancing brain‐like computing for applications in humanoid robotics, prosthetics, and wearable technologies. These systems mimic the functionalities of the central and peripheral nervous systems through the integration of sensory synaptic devices and neural network algorithms, enabling external stimuli to be converted into actionable electrical signals. This review delves into the intricate relationship between synaptic device technologies and neural network processing algorithms, highlighting their mutual influence on artificial intelligence capabilities. This study explores the latest advancements in artificial synaptic properties triggered by various stimuli, including optical, auditory, mechanical, and chemical inputs, and their subsequent processing through artificial neural networks for applications in image recognition and multimodal pattern recognition. The discussion extends to the emulation of biological perception via artificial synapses and concludes with future perspectives and challenges in neuromorphic system development, emphasizing the need for a deeper understanding of neural network processing to innovate and refine these complex systems.https://doi.org/10.1002/advs.202409568artificial synapsebio‐inspiredmachine learningneuromorphic sensory system |
| spellingShingle | Elvis K. Boahen Hyukmin Kweon Hayoung Oh Ji Hong Kim Hayoung Lim Do Hwan Kim Bio‐Inspired Neuromorphic Sensory Systems from Intelligent Perception to Nervetronics Advanced Science artificial synapse bio‐inspired machine learning neuromorphic sensory system |
| title | Bio‐Inspired Neuromorphic Sensory Systems from Intelligent Perception to Nervetronics |
| title_full | Bio‐Inspired Neuromorphic Sensory Systems from Intelligent Perception to Nervetronics |
| title_fullStr | Bio‐Inspired Neuromorphic Sensory Systems from Intelligent Perception to Nervetronics |
| title_full_unstemmed | Bio‐Inspired Neuromorphic Sensory Systems from Intelligent Perception to Nervetronics |
| title_short | Bio‐Inspired Neuromorphic Sensory Systems from Intelligent Perception to Nervetronics |
| title_sort | bio inspired neuromorphic sensory systems from intelligent perception to nervetronics |
| topic | artificial synapse bio‐inspired machine learning neuromorphic sensory system |
| url | https://doi.org/10.1002/advs.202409568 |
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