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A Biologically Inte...
A Biologically Interfaced Evolvable Organic Pattern Classifier
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- Gerasimov, Jennifer (author)
- Linköpings universitet,Laboratoriet för organisk elektronik,Tekniska fakulteten
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- Tu, Deyu (author)
- Linköpings universitet,Laboratoriet för organisk elektronik,Tekniska fakulteten
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- Hitaishi, Vivek (author)
- Linköpings universitet,Laboratoriet för organisk elektronik,Tekniska fakulteten
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- Padinhare, Harikesh (author)
- Linköpings universitet,Laboratoriet för organisk elektronik,Tekniska fakulteten
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- Yang, Chiyuan (author)
- Linköpings universitet,Laboratoriet för organisk elektronik,Tekniska fakulteten
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- Abrahamsson, Tobias (author)
- Linköpings universitet,Laboratoriet för organisk elektronik,Tekniska fakulteten
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- Karami Rad, Meysam (author)
- Linköpings universitet,Laboratoriet för organisk elektronik,Tekniska fakulteten
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- Donahue, Mary (author)
- Linköpings universitet,Laboratoriet för organisk elektronik,Tekniska fakulteten
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- Silverå Ejneby, Malin (author)
- Linköpings universitet,Avdelningen för medicinsk teknik,Tekniska fakulteten
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- Berggren, Magnus (author)
- Linköpings universitet,Laboratoriet för organisk elektronik,Tekniska fakulteten
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- Forchheimer, Robert (author)
- Linköpings universitet,Informationskodning,Tekniska fakulteten
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- Fabiano, Simone (author)
- Linköpings universitet,Laboratoriet för organisk elektronik,Tekniska fakulteten
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(creator_code:org_t)
- 2023-03-19
- 2023
- English.
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In: Advanced Science. - : WILEY. - 2198-3844. ; 10:14
- Related links:
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https://liu.diva-por... (primary) (Raw object)
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Subject headings
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- Future brain-computer interfaces will require local and highly individualized signal processing of fully integrated electronic circuits within the nervous system and other living tissue. New devices will need to be developed that can receive data from a sensor array, process these data into meaningful information, and translate that information into a format that can be interpreted by living systems. Here, the first example of interfacing a hardware-based pattern classifier with a biological nerve is reported. The classifier implements the Widrow-Hoff learning algorithm on an array of evolvable organic electrochemical transistors (EOECTs). The EOECTs channel conductance is modulated in situ by electropolymerizing the semiconductor material within the channel, allowing for low voltage operation, high reproducibility, and an improvement in state retention by two orders of magnitude over state-of-the-art OECT devices. The organic classifier is interfaced with a biological nerve using an organic electrochemical spiking neuron to translate the classifiers output to a simulated action potential. The latter is then used to stimulate muscle contraction selectively based on the input pattern, thus paving the way for the development of adaptive neural interfaces for closed-loop therapeutic systems.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Kemiteknik -- Annan kemiteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Chemical Engineering -- Other Chemical Engineering (hsv//eng)
Keyword
- conducting polymers; electropolymerization; evolvable electronics; neuromorphic hardware; organic electrochemical transistors; organic electronics; synaptic transistors
Publication and Content Type
- ref (subject category)
- art (subject category)
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- By the author/editor
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Gerasimov, Jenni ...
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Tu, Deyu
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Hitaishi, Vivek
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Padinhare, Harik ...
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Yang, Chiyuan
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Abrahamsson, Tob ...
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show more...
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Karami Rad, Meys ...
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Donahue, Mary
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Silverå Ejneby, ...
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Berggren, Magnus
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Forchheimer, Rob ...
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Fabiano, Simone
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- About the subject
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- ENGINEERING AND TECHNOLOGY
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ENGINEERING AND ...
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and Chemical Enginee ...
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and Other Chemical E ...
- Articles in the publication
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Advanced Science
- By the university
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Linköping University