Full metadata record

DC Field Value Language
dc.contributor.authorSon, Choonghyun-
dc.contributor.authorKim, Seulgee-
dc.contributor.authorKim, Seung-jong-
dc.contributor.authorChoi, Junho-
dc.contributor.authorKim, DaeEun-
dc.date.accessioned2024-01-19T22:32:27Z-
dc.date.available2024-01-19T22:32:27Z-
dc.date.created2021-09-03-
dc.date.issued2018-06-01-
dc.identifier.issn0924-4247-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/121270-
dc.description.abstractThe need to assess muscle activation and intention recognition in the design of prosthetic or exoskeleton robots has recently increased in rehabilitation medical research. Assessment of the muscle activation has an important role in the control of wearable devices. Such application requires estimating a patient's intention through the detection of their muscle activation. Previously developed techniques, namely, bioelectrical impedance analysis, electrical impedance myography, electrical impedance tomography, and a surface electromyogram, have been used in the detection of muscle activation. However, these techniques tend to have difficulty in assessing the muscle activation. A biopsy needle can be used to sense the muscle activation in an invasive manner. We propose a new method for detecting the muscle activation using multi-electrode sensing with electrical stimulation, but without a biopsy needle. Electrical stimulation is applied to the skin of a subjects forearm. The signals reflected from their muscles are then measured using multiple electrodes placed on the skin. The forearm skin and its muscles can be modeled as muscle tissue circuits depending on the signal frequency. We verified the proposed method experimentally through isometric muscle contraction, isotonic muscle action, and a frequency response test using various frequencies of the electric stimulation signals. Experiments with eight healthy subjects showed promising results in the detection of muscle activation, which can be applied to prosthetic or exoskeleton robots. (C) 2018 Elsevier B.V. All rights reserved.-
dc.languageEnglish-
dc.publisherELSEVIER SCIENCE SA-
dc.subjectBIOELECTRICAL-IMPEDANCE ANALYSIS-
dc.subjectSUBCUTANEOUS FAT-
dc.subjectMYOGRAPHY-
dc.subjectSIGNALS-
dc.subjectROBOT-
dc.subjectGAIT-
dc.subjectMASS-
dc.titleDetection of muscle activation through multi-electrode sensing using electrical stimulation-
dc.typeArticle-
dc.identifier.doi10.1016/j.sna.2018.03.030-
dc.description.journalClass1-
dc.identifier.bibliographicCitationSENSORS AND ACTUATORS A-PHYSICAL, v.275, pp.19 - 28-
dc.citation.titleSENSORS AND ACTUATORS A-PHYSICAL-
dc.citation.volume275-
dc.citation.startPage19-
dc.citation.endPage28-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.identifier.wosid000432510100003-
dc.identifier.scopusid2-s2.0-85044784577-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.relation.journalWebOfScienceCategoryInstruments & Instrumentation-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaInstruments & Instrumentation-
dc.type.docTypeArticle-
dc.subject.keywordPlusBIOELECTRICAL-IMPEDANCE ANALYSIS-
dc.subject.keywordPlusSUBCUTANEOUS FAT-
dc.subject.keywordPlusMYOGRAPHY-
dc.subject.keywordPlusSIGNALS-
dc.subject.keywordPlusROBOT-
dc.subject.keywordPlusGAIT-
dc.subject.keywordPlusMASS-
dc.subject.keywordAuthorDetection of muscle activation-
dc.subject.keywordAuthorMulti-electrode sensing-
dc.subject.keywordAuthorElectrical impedance-
dc.subject.keywordAuthorIsometric muscle action-
dc.subject.keywordAuthorIsotonic muscle movement-
Appears in Collections:
KIST Article > 2018
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML

qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE