An artificial sensory neuron with tactile perceptual learning
Sensory neurons within skin form an interface between the external physical reality and the inner tactile perception. This interface enables sensory information to be organized identified, and interpreted through perceptual learning-the process whereby the sensing abilities improve through experienc...
| Main Authors: | , , , , , , , , , , |
|---|---|
| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2020
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/137788 |
| _version_ | 1824455504954392576 |
|---|---|
| author | Wan, Changjin Chen, Geng Fu, Yangming Wang, Ming Matsuhisa, Naoji Pan, Shaowu Pan, Liang Yang, Hui Wan, Qing Zhu, Liqiang Chen, Xiaodong |
| author2 | School of Materials Science & Engineering |
| author_facet | School of Materials Science & Engineering Wan, Changjin Chen, Geng Fu, Yangming Wang, Ming Matsuhisa, Naoji Pan, Shaowu Pan, Liang Yang, Hui Wan, Qing Zhu, Liqiang Chen, Xiaodong |
| author_sort | Wan, Changjin |
| collection | NTU |
| description | Sensory neurons within skin form an interface between the external physical reality and the inner tactile perception. This interface enables sensory information to be organized identified, and interpreted through perceptual learning-the process whereby the sensing abilities improve through experience. Here, an artificial sensory neuron that can integrate and differentiate the spatiotemporal features of touched patterns for recognition is shown. The system comprises sensing, transmitting, and processing components that are parallel to those found in a sensory neuron. A resistive pressure sensor converts pressure stimuli into electric signals, which are transmitted to a synaptic transistor through interfacial ionic/electronic coupling via a soft ionic conductor. Furthermore, the recognition error rate can be dramatically decreased from 44% to 0.4% by integrating with the machine learning method. This work represents a step toward the design and use of neuromorphic electronic skin with artificial intelligence for robotics and prosthetics. |
| first_indexed | 2025-02-19T03:39:16Z |
| format | Journal Article |
| id | ntu-10356/137788 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T03:39:16Z |
| publishDate | 2020 |
| record_format | dspace |
| spelling | ntu-10356/1377882023-07-14T15:54:18Z An artificial sensory neuron with tactile perceptual learning Wan, Changjin Chen, Geng Fu, Yangming Wang, Ming Matsuhisa, Naoji Pan, Shaowu Pan, Liang Yang, Hui Wan, Qing Zhu, Liqiang Chen, Xiaodong School of Materials Science & Engineering Innovative Center for Flexible Devices Engineering::Materials Artificial Intelligence Artificial Neurons Sensory neurons within skin form an interface between the external physical reality and the inner tactile perception. This interface enables sensory information to be organized identified, and interpreted through perceptual learning-the process whereby the sensing abilities improve through experience. Here, an artificial sensory neuron that can integrate and differentiate the spatiotemporal features of touched patterns for recognition is shown. The system comprises sensing, transmitting, and processing components that are parallel to those found in a sensory neuron. A resistive pressure sensor converts pressure stimuli into electric signals, which are transmitted to a synaptic transistor through interfacial ionic/electronic coupling via a soft ionic conductor. Furthermore, the recognition error rate can be dramatically decreased from 44% to 0.4% by integrating with the machine learning method. This work represents a step toward the design and use of neuromorphic electronic skin with artificial intelligence for robotics and prosthetics. NRF (Natl Research Foundation, S’pore) MOE (Min. of Education, S’pore) Accepted version 2020-04-15T02:10:13Z 2020-04-15T02:10:13Z 2018 Journal Article Wan, C., Chen, G., Fu, Y., Wang, M., Matsuhisa, N., Pan, S., . . ., Chen, X. (2018). An artificial sensory neuron with tactile perceptual learning. Advanced materials, 30(30), 1801291-. doi:10.1002/adma.201801291 0935-9648 https://hdl.handle.net/10356/137788 10.1002/adma.201801291 29882255 2-s2.0-85050394157 30 30 en Advanced materials © 2018 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim. All rights reserved. This paper was published in Advanced materials and is made available with permission of WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim. application/pdf |
| spellingShingle | Engineering::Materials Artificial Intelligence Artificial Neurons Wan, Changjin Chen, Geng Fu, Yangming Wang, Ming Matsuhisa, Naoji Pan, Shaowu Pan, Liang Yang, Hui Wan, Qing Zhu, Liqiang Chen, Xiaodong An artificial sensory neuron with tactile perceptual learning |
| title | An artificial sensory neuron with tactile perceptual learning |
| title_full | An artificial sensory neuron with tactile perceptual learning |
| title_fullStr | An artificial sensory neuron with tactile perceptual learning |
| title_full_unstemmed | An artificial sensory neuron with tactile perceptual learning |
| title_short | An artificial sensory neuron with tactile perceptual learning |
| title_sort | artificial sensory neuron with tactile perceptual learning |
| topic | Engineering::Materials Artificial Intelligence Artificial Neurons |
| url | https://hdl.handle.net/10356/137788 |
| work_keys_str_mv | AT wanchangjin anartificialsensoryneuronwithtactileperceptuallearning AT chengeng anartificialsensoryneuronwithtactileperceptuallearning AT fuyangming anartificialsensoryneuronwithtactileperceptuallearning AT wangming anartificialsensoryneuronwithtactileperceptuallearning AT matsuhisanaoji anartificialsensoryneuronwithtactileperceptuallearning AT panshaowu anartificialsensoryneuronwithtactileperceptuallearning AT panliang anartificialsensoryneuronwithtactileperceptuallearning AT yanghui anartificialsensoryneuronwithtactileperceptuallearning AT wanqing anartificialsensoryneuronwithtactileperceptuallearning AT zhuliqiang anartificialsensoryneuronwithtactileperceptuallearning AT chenxiaodong anartificialsensoryneuronwithtactileperceptuallearning AT wanchangjin artificialsensoryneuronwithtactileperceptuallearning AT chengeng artificialsensoryneuronwithtactileperceptuallearning AT fuyangming artificialsensoryneuronwithtactileperceptuallearning AT wangming artificialsensoryneuronwithtactileperceptuallearning AT matsuhisanaoji artificialsensoryneuronwithtactileperceptuallearning AT panshaowu artificialsensoryneuronwithtactileperceptuallearning AT panliang artificialsensoryneuronwithtactileperceptuallearning AT yanghui artificialsensoryneuronwithtactileperceptuallearning AT wanqing artificialsensoryneuronwithtactileperceptuallearning AT zhuliqiang artificialsensoryneuronwithtactileperceptuallearning AT chenxiaodong artificialsensoryneuronwithtactileperceptuallearning |