Research progress on analysis methods in electroencephalography-electromyography synchronous coupling
The motor nervous system transmits motion control information through nervous oscillations, which causes the synchronous oscillatory activity of the corresponding muscle to reflect the motion response information and give the cerebral cortex feedback, so that it can sense the state of the limbs. Thi...
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| Veröffentlicht in: | Sheng wu yi xue gong cheng xue za zhi 2019-04, Vol.36 (2), p.334-337 |
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| container_title | Sheng wu yi xue gong cheng xue za zhi |
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| creator | Li, Sujiao Liu, Su Lan, He Yu, Hongliu |
| description | The motor nervous system transmits motion control information through nervous oscillations, which causes the synchronous oscillatory activity of the corresponding muscle to reflect the motion response information and give the cerebral cortex feedback, so that it can sense the state of the limbs. This synchronous oscillatory activity can reflect connectivity information of electroencephalography-electromyography (EEG-EMG) functional coupling. The strength of the coupling is determined by various factors including the strength of muscle contraction, attention, motion intention etc. It is very significant to study motor functional evaluation and control methods to analyze the changes of EEG-EMG synchronous coupling caused by different factors. This article mainly introduces and compares coherence and Granger causality of linear methods, the mutual information and transfer entropy of nonlinear methods in EEG-EMG synchronous coupling, and summarizes the application of each method, so that researchers in related fields can understand the current research progress on analysis methods of EEG-EMG synchronous systematically. |
| doi_str_mv | 10.7507/1001-5515.201804005 |
| format | Article |
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This synchronous oscillatory activity can reflect connectivity information of electroencephalography-electromyography (EEG-EMG) functional coupling. The strength of the coupling is determined by various factors including the strength of muscle contraction, attention, motion intention etc. It is very significant to study motor functional evaluation and control methods to analyze the changes of EEG-EMG synchronous coupling caused by different factors. This article mainly introduces and compares coherence and Granger causality of linear methods, the mutual information and transfer entropy of nonlinear methods in EEG-EMG synchronous coupling, and summarizes the application of each method, so that researchers in related fields can understand the current research progress on analysis methods of EEG-EMG synchronous systematically.</description><identifier>ISSN: 1001-5515</identifier><identifier>DOI: 10.7507/1001-5515.201804005</identifier><identifier>PMID: 31016953</identifier><language>chi</language><publisher>China: Sichuan Society for Biomedical Engineering</publisher><subject>Cerebral cortex ; Control methods ; Coupling ; EEG ; Electroencephalography ; Electromyography ; Entropy (Information theory) ; Humans ; Information systems ; Motion control ; Motor Cortex - physiology ; Motor task performance ; Muscle contraction ; Muscle, Skeletal - physiology ; Muscles ; Muscular function ; Nervous system ; Oscillations</subject><ispartof>Sheng wu yi xue gong cheng xue za zhi, 2019-04, Vol.36 (2), p.334-337</ispartof><rights>Copyright Sichuan Society for Biomedical Engineering 2019</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c1343-80035587cbfb46578c022f84f21213133ff61af780c23139dfd6c0990f7f86893</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31016953$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Li, Sujiao</creatorcontrib><creatorcontrib>Liu, Su</creatorcontrib><creatorcontrib>Lan, He</creatorcontrib><creatorcontrib>Yu, Hongliu</creatorcontrib><title>Research progress on analysis methods in electroencephalography-electromyography synchronous coupling</title><title>Sheng wu yi xue gong cheng xue za zhi</title><addtitle>Sheng Wu Yi Xue Gong Cheng Xue Za Zhi</addtitle><description>The motor nervous system transmits motion control information through nervous oscillations, which causes the synchronous oscillatory activity of the corresponding muscle to reflect the motion response information and give the cerebral cortex feedback, so that it can sense the state of the limbs. This synchronous oscillatory activity can reflect connectivity information of electroencephalography-electromyography (EEG-EMG) functional coupling. The strength of the coupling is determined by various factors including the strength of muscle contraction, attention, motion intention etc. It is very significant to study motor functional evaluation and control methods to analyze the changes of EEG-EMG synchronous coupling caused by different factors. This article mainly introduces and compares coherence and Granger causality of linear methods, the mutual information and transfer entropy of nonlinear methods in EEG-EMG synchronous coupling, and summarizes the application of each method, so that researchers in related fields can understand the current research progress on analysis methods of EEG-EMG synchronous systematically.</description><subject>Cerebral cortex</subject><subject>Control methods</subject><subject>Coupling</subject><subject>EEG</subject><subject>Electroencephalography</subject><subject>Electromyography</subject><subject>Entropy (Information theory)</subject><subject>Humans</subject><subject>Information systems</subject><subject>Motion control</subject><subject>Motor Cortex - physiology</subject><subject>Motor task performance</subject><subject>Muscle contraction</subject><subject>Muscle, Skeletal - physiology</subject><subject>Muscles</subject><subject>Muscular function</subject><subject>Nervous system</subject><subject>Oscillations</subject><issn>1001-5515</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpdkE1LxDAQhnNQ3GXdXyBIwIuXrpOkadOjLH7BgiB6LmmabCttUpP20H9vFqsHT8O8PDzMOwhdEdjlHPI7AkASzgnfUSACUgB-htZ_6QptQ2grACogywS7QCtGgGQFZ2uk33TQ0qsGD94dvQ4BO4ulld0c2oB7PTauDri1WHdajd5pq_TQyC7CcmjmZIn7eQlwmK1qvLNuCli5aehae7xE50Z2QW-XuUEfjw_v--fk8Pr0sr8_JIqwlCUCgHEuclWZKs14LhRQakRqKKGEEcaMyYg0uQBF41rUps4UFAWY3IhMFGyDbn-8sczXpMNY9m1Quuuk1fGekkZNwaL6hN78Qz_d5GPvEyVoypiI8AZdL9RU9bouB9_20s_l7wPZN9Whcmo</recordid><startdate>20190425</startdate><enddate>20190425</enddate><creator>Li, Sujiao</creator><creator>Liu, Su</creator><creator>Lan, He</creator><creator>Yu, Hongliu</creator><general>Sichuan Society for Biomedical Engineering</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>7QO</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>7X8</scope></search><sort><creationdate>20190425</creationdate><title>Research progress on analysis methods in electroencephalography-electromyography synchronous coupling</title><author>Li, Sujiao ; Liu, Su ; Lan, He ; Yu, Hongliu</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1343-80035587cbfb46578c022f84f21213133ff61af780c23139dfd6c0990f7f86893</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>chi</language><creationdate>2019</creationdate><topic>Cerebral cortex</topic><topic>Control methods</topic><topic>Coupling</topic><topic>EEG</topic><topic>Electroencephalography</topic><topic>Electromyography</topic><topic>Entropy (Information theory)</topic><topic>Humans</topic><topic>Information systems</topic><topic>Motion control</topic><topic>Motor Cortex - physiology</topic><topic>Motor task performance</topic><topic>Muscle contraction</topic><topic>Muscle, Skeletal - physiology</topic><topic>Muscles</topic><topic>Muscular function</topic><topic>Nervous system</topic><topic>Oscillations</topic><toplevel>online_resources</toplevel><creatorcontrib>Li, Sujiao</creatorcontrib><creatorcontrib>Liu, Su</creatorcontrib><creatorcontrib>Lan, He</creatorcontrib><creatorcontrib>Yu, Hongliu</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>Biotechnology Research Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Sheng wu yi xue gong cheng xue za zhi</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Sujiao</au><au>Liu, Su</au><au>Lan, He</au><au>Yu, Hongliu</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Research progress on analysis methods in electroencephalography-electromyography synchronous coupling</atitle><jtitle>Sheng wu yi xue gong cheng xue za zhi</jtitle><addtitle>Sheng Wu Yi Xue Gong Cheng Xue Za Zhi</addtitle><date>2019-04-25</date><risdate>2019</risdate><volume>36</volume><issue>2</issue><spage>334</spage><epage>337</epage><pages>334-337</pages><issn>1001-5515</issn><abstract>The motor nervous system transmits motion control information through nervous oscillations, which causes the synchronous oscillatory activity of the corresponding muscle to reflect the motion response information and give the cerebral cortex feedback, so that it can sense the state of the limbs. This synchronous oscillatory activity can reflect connectivity information of electroencephalography-electromyography (EEG-EMG) functional coupling. The strength of the coupling is determined by various factors including the strength of muscle contraction, attention, motion intention etc. It is very significant to study motor functional evaluation and control methods to analyze the changes of EEG-EMG synchronous coupling caused by different factors. This article mainly introduces and compares coherence and Granger causality of linear methods, the mutual information and transfer entropy of nonlinear methods in EEG-EMG synchronous coupling, and summarizes the application of each method, so that researchers in related fields can understand the current research progress on analysis methods of EEG-EMG synchronous systematically.</abstract><cop>China</cop><pub>Sichuan Society for Biomedical Engineering</pub><pmid>31016953</pmid><doi>10.7507/1001-5515.201804005</doi><tpages>4</tpages></addata></record> |
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| subjects | Cerebral cortex Control methods Coupling EEG Electroencephalography Electromyography Entropy (Information theory) Humans Information systems Motion control Motor Cortex - physiology Motor task performance Muscle contraction Muscle, Skeletal - physiology Muscles Muscular function Nervous system Oscillations |
| title | Research progress on analysis methods in electroencephalography-electromyography synchronous coupling |
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