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DC Field | Value | Language |
---|---|---|
dc.citation.endPage | 151328 | - |
dc.citation.startPage | 151320 | - |
dc.citation.title | IEEE ACCESS | - |
dc.citation.volume | 7 | - |
dc.contributor.author | Chae, Hee Young | - |
dc.contributor.author | Lee, Kwangmuk | - |
dc.contributor.author | Jang, Jonggyu | - |
dc.contributor.author | Park, Kyeonghwan | - |
dc.contributor.author | Kim, Jae Joon | - |
dc.date.accessioned | 2023-12-21T18:38:56Z | - |
dc.date.available | 2023-12-21T18:38:56Z | - |
dc.date.created | 2019-10-19 | - |
dc.date.issued | 2019-10 | - |
dc.description.abstract | This paper presents a wearable wireless surface electromyogram (sEMG) integrated interface that utilizes a proposed analog pseudo-wavelet preprocessor (APWP) for signal acquisition and pattern recognition. The APWP is integrated into a readout integrated circuit (ROIC), which is fabricated in a 0.18-μm complementary metal-oxide-semiconductor (CMOS) process. Based on this ROIC, a wearable device module and its wireless system prototype are implemented to recognize five kinds of real-time hand-gesture motions, where the power consumption is further reduced by adopting low-power components. Real-time measurements of sEMG signals and APWP data through this wearable interface are wirelessly transferred to a laptop or a sensor hub, and then they are further processed to implement the pseudo-wavelet transform under the MATLAB environment. The resulting APWP-augmented pattern-recognition algorithm was experimentally verified to improve the accuracy by 7 % with a real-time frequency analysis. | - |
dc.identifier.bibliographicCitation | IEEE ACCESS, v.7, pp.151320 - 151328 | - |
dc.identifier.doi | 10.1109/ACCESS.2019.2948090 | - |
dc.identifier.issn | 2169-3536 | - |
dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/28971 | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/8873561 | - |
dc.identifier.wosid | 000497163000073 | - |
dc.language | 영어 | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | A Wearable sEMG Pattern-Recognition Integrated Interface Embedding Analog Pseudo-Wavelet Preprocessing | - |
dc.type | Article | - |
dc.description.isOpenAccess | FALSE | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems; Engineering, Electrical & Electronic; Telecommunications | - |
dc.relation.journalResearchArea | Computer Science; Engineering; Telecommunications | - |
dc.type.docType | Article | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordAuthor | Pattern recognition | - |
dc.subject.keywordAuthor | Real-time systems | - |
dc.subject.keywordAuthor | Wireless communication | - |
dc.subject.keywordAuthor | Power demand | - |
dc.subject.keywordAuthor | Wireless sensor networks | - |
dc.subject.keywordAuthor | Wavelet transforms | - |
dc.subject.keywordAuthor | Frequency-domain analysis | - |
dc.subject.keywordAuthor | Surface electromyogram | - |
dc.subject.keywordAuthor | pattern recognition | - |
dc.subject.keywordAuthor | readout integrated circuit | - |
dc.subject.keywordAuthor | analog wavelet preprocessor | - |
dc.subject.keywordAuthor | wireless sensor interface | - |
dc.subject.keywordPlus | LOW-POWER | - |
dc.subject.keywordPlus | TIME | - |
dc.subject.keywordPlus | APPROXIMATION | - |
dc.subject.keywordPlus | AMPLIFIER | - |
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