Expert committee classifier for hand motions recognition from EMG signals
This paper presents the design and implementation of a novel technique for the recognition of four hand motions for real time response (flexion (FL), extension (EX), opening (OP) and closure (CL)) from electromyographic (EMG) signals generated from two forearm muscles: palmaris longus and extensor d...
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| Veröffentlicht in: | Ingeniare : Revista Chilena de Ingenieria 2018-03, Vol.26 (1), p.62-71 |
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| container_title | Ingeniare : Revista Chilena de Ingenieria |
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| creator | Reyes López, David A. Loaiza Correa, Humberto Arias López, Mauricio Duarte Sánchez, Jorge E. |
| description | This paper presents the design and implementation of a novel technique for the recognition of four hand motions for real time response (flexion (FL), extension (EX), opening (OP) and closure (CL)) from electromyographic (EMG) signals generated from two forearm muscles: palmaris longus and extensor digitorum. The development of the work had two main stages: the low cost hardware for acquisition and conditioning of the EMG analog signals and the processing system for the identification and classification of the movement performed for real time response; the entire system was integrated in a hardware-software application using MATLAB and processing techniques for the discriminant analysis were performed. Three methods were evaluated for pattern recognition getting 98% recognition rates with the method proposed which had the best performance. |
| doi_str_mv | 10.4067/S0718-33052018000100062 |
| format | Article |
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The development of the work had two main stages: the low cost hardware for acquisition and conditioning of the EMG analog signals and the processing system for the identification and classification of the movement performed for real time response; the entire system was integrated in a hardware-software application using MATLAB and processing techniques for the discriminant analysis were performed. Three methods were evaluated for pattern recognition getting 98% recognition rates with the method proposed which had the best performance.</description><identifier>ISSN: 0718-3305</identifier><identifier>ISSN: 0718-3291</identifier><identifier>EISSN: 0718-3305</identifier><identifier>DOI: 10.4067/S0718-33052018000100062</identifier><language>eng</language><publisher>Arica: Universidad de Tarapacá</publisher><subject>Discriminant analysis ; Electromyography ; ENGINEERING, MULTIDISCIPLINARY ; Forearm ; Hardware ; Matlab ; Muscles ; Neural networks ; Pattern recognition ; Real time ; Time response</subject><ispartof>Ingeniare : Revista Chilena de Ingenieria, 2018-03, Vol.26 (1), p.62-71</ispartof><rights>Copyright Universidad de Tarapacá Mar 2018</rights><rights>This work is licensed under a Creative Commons Attribution 4.0 International License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3422-d39b60112d1f9f2d9ac389abac927f2d7eaaa1876dd1169552396fe93ace64f73</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27923,27924</link.rule.ids></links><search><creatorcontrib>Reyes López, David A.</creatorcontrib><creatorcontrib>Loaiza Correa, Humberto</creatorcontrib><creatorcontrib>Arias López, Mauricio</creatorcontrib><creatorcontrib>Duarte Sánchez, Jorge E.</creatorcontrib><title>Expert committee classifier for hand motions recognition from EMG signals</title><title>Ingeniare : Revista Chilena de Ingenieria</title><addtitle>Ingeniare. 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Loaiza Correa, Humberto ; Arias López, Mauricio ; Duarte Sánchez, Jorge E.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3422-d39b60112d1f9f2d9ac389abac927f2d7eaaa1876dd1169552396fe93ace64f73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Discriminant analysis</topic><topic>Electromyography</topic><topic>ENGINEERING, MULTIDISCIPLINARY</topic><topic>Forearm</topic><topic>Hardware</topic><topic>Matlab</topic><topic>Muscles</topic><topic>Neural networks</topic><topic>Pattern recognition</topic><topic>Real time</topic><topic>Time response</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Reyes López, David A.</creatorcontrib><creatorcontrib>Loaiza Correa, Humberto</creatorcontrib><creatorcontrib>Arias López, Mauricio</creatorcontrib><creatorcontrib>Duarte Sánchez, Jorge E.</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Docstoc</collection><collection>University Readers</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>Latin America & Iberia Database</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Research Library</collection><collection>Engineering Database</collection><collection>Research Library (Corporate)</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>ProQuest Central Basic</collection><collection>SciELO</collection><jtitle>Ingeniare : Revista Chilena de Ingenieria</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Reyes López, David A.</au><au>Loaiza Correa, Humberto</au><au>Arias López, Mauricio</au><au>Duarte Sánchez, Jorge E.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Expert committee classifier for hand motions recognition from EMG signals</atitle><jtitle>Ingeniare : Revista Chilena de Ingenieria</jtitle><addtitle>Ingeniare. Rev. chil. ing</addtitle><date>2018-03</date><risdate>2018</risdate><volume>26</volume><issue>1</issue><spage>62</spage><epage>71</epage><pages>62-71</pages><issn>0718-3305</issn><issn>0718-3291</issn><eissn>0718-3305</eissn><abstract>This paper presents the design and implementation of a novel technique for the recognition of four hand motions for real time response (flexion (FL), extension (EX), opening (OP) and closure (CL)) from electromyographic (EMG) signals generated from two forearm muscles: palmaris longus and extensor digitorum. The development of the work had two main stages: the low cost hardware for acquisition and conditioning of the EMG analog signals and the processing system for the identification and classification of the movement performed for real time response; the entire system was integrated in a hardware-software application using MATLAB and processing techniques for the discriminant analysis were performed. Three methods were evaluated for pattern recognition getting 98% recognition rates with the method proposed which had the best performance.</abstract><cop>Arica</cop><pub>Universidad de Tarapacá</pub><doi>10.4067/S0718-33052018000100062</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | Ingeniare : Revista Chilena de Ingenieria, 2018-03, Vol.26 (1), p.62-71 |
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| source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
| subjects | Discriminant analysis Electromyography ENGINEERING, MULTIDISCIPLINARY Forearm Hardware Matlab Muscles Neural networks Pattern recognition Real time Time response |
| title | Expert committee classifier for hand motions recognition from EMG signals |
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