Co-integrated Neuromorphic Devices for Bio-inspired Compliance Control

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dc.contributor.authorShin, Heryko
dc.contributor.authorYu, Ji-Manko
dc.contributor.authorHan, Joon-Kyuko
dc.contributor.authorChoi, Yang-Kyuko
dc.date.accessioned2023-11-13T09:00:23Z-
dc.date.available2023-11-13T09:00:23Z-
dc.date.created2023-10-11-
dc.date.issued2023-11-
dc.identifier.citationIEEE TRANSACTIONS ON NANOTECHNOLOGY, v.22, pp.706 - 712-
dc.identifier.issn1536-125X-
dc.identifier.urihttp://hdl.handle.net/10203/314532-
dc.description.abstractMutual interactions between humans and devices are being widely adopted, including wearable electromechanical devices known as robotic exoskeletons. Among various modules used to control the human-robot interactions, compliance control (CC) is needed to ensure human safety and avoid abnormal operations. Here we propose a novel CC system with co-integrated neuromorphic devices composed of a pre-synapse, an interneuron, and a post-synapse. These devices are the same homotypic MOSFET with a SONOS configuration, despite having different functions. For proof-of-concept, semi-empirical simulations were conducted with the aid of an LTspice simulator, by reflecting measured neuron and synapse characteristics from the fabricated tri-gate FinFETs. The extremely low-power consumption of 0.2 mW, which is 55-fold smaller than other conventional approaches, was achieved. A high response rate of up to 3 ms was attained as well. Moreover, by automatically adjusting output signal frequency and amplitude, the micro-sized neuromorphic CC system can avoid excess actuator motion in human-robot interactions.-
dc.languageEnglish-
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC-
dc.titleCo-integrated Neuromorphic Devices for Bio-inspired Compliance Control-
dc.typeArticle-
dc.identifier.wosid001090964100002-
dc.identifier.scopusid2-s2.0-85174811691-
dc.type.rimsART-
dc.citation.volume22-
dc.citation.beginningpage706-
dc.citation.endingpage712-
dc.citation.publicationnameIEEE TRANSACTIONS ON NANOTECHNOLOGY-
dc.identifier.doi10.1109/TNANO.2023.3323667-
dc.contributor.localauthorChoi, Yang-Kyu-
dc.contributor.nonIdAuthorShin, Hery-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorNeurons-
dc.subject.keywordAuthorNeuromorphics-
dc.subject.keywordAuthorSynapses-
dc.subject.keywordAuthorLogic gates-
dc.subject.keywordAuthorSilicon-
dc.subject.keywordAuthorRobot sensing systems-
dc.subject.keywordAuthorVoltage measurement-
dc.subject.keywordAuthorCompliance control-
dc.subject.keywordAuthorhuman-robot interaction-
dc.subject.keywordAuthorleaky-integrate-fire-
dc.subject.keywordAuthorneuromorphic-
dc.subject.keywordAuthorneuron-
dc.subject.keywordAuthorsynapse-
dc.subject.keywordAuthorSONOS-
dc.subject.keywordPlusNEURONAL OSCILLATIONS-
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