A bioinspired flexible organic artificial afferent nerve

Author:

Kim Yeongin1ORCID,Chortos Alex2,Xu Wentao34ORCID,Liu Yuxin5,Oh Jin Young67ORCID,Son Donghee6,Kang Jiheong6,Foudeh Amir M.6,Zhu Chenxin1,Lee Yeongjun3ORCID,Niu Simiao6,Liu Jia6ORCID,Pfattner Raphael6ORCID,Bao Zhenan6ORCID,Lee Tae-Woo3ORCID

Affiliation:

1. Department of Electrical Engineering, Stanford University, Stanford, CA, USA.

2. Department of Materials Science and Engineering, Stanford University, Stanford, CA, USA.

3. Department of Materials Science and Engineering, Seoul National University, Seoul, South Korea.

4. Institute of Photoelectronic Thin Film Devices and Technology, Nankai University, Tianjin, China.

5. Department of Bioengineering, Stanford University, Stanford, CA, USA.

6. Department of Chemical Engineering, Stanford University, Stanford, CA, USA.

7. Department of Chemical Engineering, Kyung Hee University, Yongin, South Korea.

Abstract

I've got a feeling Sensory (or afferent) nerves bring sensations of touch, pain, or temperature variation to the central nervous system and brain. Using the tools and materials of organic electronics, Kim et al. combined a pressure sensor, a ring oscillator, and an ion gel–gated transistor to form an artificial mechanoreceptor (see the Perspective by Bartolozzi). The combination allows for the sensing of multiple pressure inputs, which can be converted into a sensor signal and used to drive the motion of a cockroach leg in an oscillatory pattern. Science , this issue p. 998 ; see also p. 966

Funder

National Science Foundation

Samsung Electronics

Korea government

Agency for Science Technology and Research Singapore

Creative-Pioneering Researchers Program through Seoul National University

Marie Curie Cofund, Beatriu de Pinós fellowship

Natural Sciences and Engineering Research Council (NSERC) of Canada

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

Reference37 articles.

1. Large-scale neuromorphic computing systems

2. The SpiNNaker Project

3. J. Schemmel D. Briiderle A. Griibl M. Hock K. Meier S. Millner paper presented at the 2010 IEEE International Symposium on Circuits and Systems (ISCAS2010) Paris France 30 May to 2 June 2010.

4. A reconfigurable on-line learning spiking neuromorphic processor comprising 256 neurons and 128K synapses

5. C. Mead Analog VLSI and Neural Systems (Addison-Wesley Longman 1989).

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