Prediction of Larynx Function Using Multichannel Surface EMG Classification
Total laryngectomy (TL) affects critical functions such as swallowing, coughing and speaking. An artificial, bioengineered larynx (ABL), operated via myoelectric signals, may improve quality of life for TL patients. To evaluate the efficacy of using surface electromyography (sEMG) as a control signa...
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Veröffentlicht in: | IEEE transactions on medical robotics and bionics 2021-11, Vol.3 (4), p.1032-1039 |
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creator | McNulty, Johnny de Jager, Kylie Lancashire, Henry T. Graveston, James Birchall, Martin Vanhoestenberghe, Anne |
description | Total laryngectomy (TL) affects critical functions such as swallowing, coughing and speaking. An artificial, bioengineered larynx (ABL), operated via myoelectric signals, may improve quality of life for TL patients. To evaluate the efficacy of using surface electromyography (sEMG) as a control signal to predict instances of swallowing, coughing and speaking, sEMG was recorded from submental, intercostal and diaphragm muscles. The cohort included TL and control participants. Swallowing, coughing, speaking and movement actions were recorded, and a range of classifiers were investigated for prediction of these actions. Our algorithm achieved F1-scores of 76.0 ± 4.4% (swallows), 93.8 ± 2.8% (coughs) and 70.5 ± 5.4% (speech) for controls, and 67.7 ± 4.4% (swallows), 71.0 ± 9.1% (coughs) and 78.0 ± 3.8% (speech) for TLs, using a random forest (RF) classifier. 75.1 ± 6.9% of swallows were detected within 500 ms of onset in the controls, and 63.1 ± 6.1% in TLs. sEMG can be used to predict critical larynx movements, although a viable ABL requires improvements. Results are particularly encouraging as they encompass a TL cohort. An ABL could alleviate many challenges faced by laryngectomees. This study represents a promising step toward realising such a device. |
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An artificial, bioengineered larynx (ABL), operated via myoelectric signals, may improve quality of life for TL patients. To evaluate the efficacy of using surface electromyography (sEMG) as a control signal to predict instances of swallowing, coughing and speaking, sEMG was recorded from submental, intercostal and diaphragm muscles. The cohort included TL and control participants. Swallowing, coughing, speaking and movement actions were recorded, and a range of classifiers were investigated for prediction of these actions. Our algorithm achieved F1-scores of 76.0 ± 4.4% (swallows), 93.8 ± 2.8% (coughs) and 70.5 ± 5.4% (speech) for controls, and 67.7 ± 4.4% (swallows), 71.0 ± 9.1% (coughs) and 78.0 ± 3.8% (speech) for TLs, using a random forest (RF) classifier. 75.1 ± 6.9% of swallows were detected within 500 ms of onset in the controls, and 63.1 ± 6.1% in TLs. sEMG can be used to predict critical larynx movements, although a viable ABL requires improvements. Results are particularly encouraging as they encompass a TL cohort. An ABL could alleviate many challenges faced by laryngectomees. This study represents a promising step toward realising such a device.</description><identifier>ISSN: 2576-3202</identifier><identifier>EISSN: 2576-3202</identifier><identifier>DOI: 10.1109/TMRB.2021.3122966</identifier><identifier>PMID: 34901764</identifier><language>eng</language><publisher>United States: IEEE</publisher><subject>Algorithms ; Artificial larynx ; Bioengineering ; Classifiers ; coughing ; Electromyography ; Larynx ; Muscles ; Myoelectricity ; Pattern recognition ; Signal quality ; Speaking ; Speech ; surface electromyography (sEMG) ; Swallowing ; total laryngectomy</subject><ispartof>IEEE transactions on medical robotics and bionics, 2021-11, Vol.3 (4), p.1032-1039</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c447t-49fc05831db4b57c4ba76ea264bf9638103c09f8aa5fa764a5b5e706229c83f93</citedby><cites>FETCH-LOGICAL-c447t-49fc05831db4b57c4ba76ea264bf9638103c09f8aa5fa764a5b5e706229c83f93</cites><orcidid>0000-0002-7244-5864 ; 0000-0002-8428-7752 ; 0000-0002-1377-7439</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9585573$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>230,314,780,784,796,885,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9585573$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34901764$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>McNulty, Johnny</creatorcontrib><creatorcontrib>de Jager, Kylie</creatorcontrib><creatorcontrib>Lancashire, Henry T.</creatorcontrib><creatorcontrib>Graveston, James</creatorcontrib><creatorcontrib>Birchall, Martin</creatorcontrib><creatorcontrib>Vanhoestenberghe, Anne</creatorcontrib><title>Prediction of Larynx Function Using Multichannel Surface EMG Classification</title><title>IEEE transactions on medical robotics and bionics</title><addtitle>TMRB</addtitle><addtitle>IEEE Trans Med Robot Bionics</addtitle><description>Total laryngectomy (TL) affects critical functions such as swallowing, coughing and speaking. An artificial, bioengineered larynx (ABL), operated via myoelectric signals, may improve quality of life for TL patients. To evaluate the efficacy of using surface electromyography (sEMG) as a control signal to predict instances of swallowing, coughing and speaking, sEMG was recorded from submental, intercostal and diaphragm muscles. The cohort included TL and control participants. Swallowing, coughing, speaking and movement actions were recorded, and a range of classifiers were investigated for prediction of these actions. Our algorithm achieved F1-scores of 76.0 ± 4.4% (swallows), 93.8 ± 2.8% (coughs) and 70.5 ± 5.4% (speech) for controls, and 67.7 ± 4.4% (swallows), 71.0 ± 9.1% (coughs) and 78.0 ± 3.8% (speech) for TLs, using a random forest (RF) classifier. 75.1 ± 6.9% of swallows were detected within 500 ms of onset in the controls, and 63.1 ± 6.1% in TLs. sEMG can be used to predict critical larynx movements, although a viable ABL requires improvements. Results are particularly encouraging as they encompass a TL cohort. An ABL could alleviate many challenges faced by laryngectomees. This study represents a promising step toward realising such a device.</description><subject>Algorithms</subject><subject>Artificial larynx</subject><subject>Bioengineering</subject><subject>Classifiers</subject><subject>coughing</subject><subject>Electromyography</subject><subject>Larynx</subject><subject>Muscles</subject><subject>Myoelectricity</subject><subject>Pattern recognition</subject><subject>Signal quality</subject><subject>Speaking</subject><subject>Speech</subject><subject>surface electromyography (sEMG)</subject><subject>Swallowing</subject><subject>total laryngectomy</subject><issn>2576-3202</issn><issn>2576-3202</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpdkd1LHDEUxYNUVNQ_oBTKQF_6suvN9-Sl0C5-4S5Kq88hk000MpvRZEb0vzfDbhfbp4R7fvdwDwehzximGIM6uV38_jUlQPCUYkKUEDvogHApJrQMP33476PjnB8BCspBUrGH9ilTgKVgB-jqJrllsH3oYtX5am7SW3ytzoa4Ht3lEO-rxdD2wT6YGF1b_RmSN9ZVp4vzataanIMP1oz0Edr1ps3uePMeoruz09vZxWR-fX45-zmfWMZkP2HKW-A1xcuGNVxa1hgpnCGCNV4JWmOgFpSvjeG-KMzwhjsJooS0NfWKHqIfa9-noVm5pXWxT6bVTymsyvm6M0H_q8TwoO-7Fy0FJlDjYvB9Y5C658HlXq9Ctq5tTXTdkDURGEBKILSg3_5DH7shxRJPE64UAS7oeBFeUzZ1OSfnt8dg0GNbemxLj23pTVtl5-vHFNuNv90U4MsaCM65rax4zbmk9B3Wmphn</recordid><startdate>20211101</startdate><enddate>20211101</enddate><creator>McNulty, Johnny</creator><creator>de Jager, Kylie</creator><creator>Lancashire, Henry T.</creator><creator>Graveston, James</creator><creator>Birchall, Martin</creator><creator>Vanhoestenberghe, Anne</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>K9.</scope><scope>L7M</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-7244-5864</orcidid><orcidid>https://orcid.org/0000-0002-8428-7752</orcidid><orcidid>https://orcid.org/0000-0002-1377-7439</orcidid></search><sort><creationdate>20211101</creationdate><title>Prediction of Larynx Function Using Multichannel Surface EMG Classification</title><author>McNulty, Johnny ; de Jager, Kylie ; Lancashire, Henry T. ; Graveston, James ; Birchall, Martin ; Vanhoestenberghe, Anne</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c447t-49fc05831db4b57c4ba76ea264bf9638103c09f8aa5fa764a5b5e706229c83f93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>Artificial larynx</topic><topic>Bioengineering</topic><topic>Classifiers</topic><topic>coughing</topic><topic>Electromyography</topic><topic>Larynx</topic><topic>Muscles</topic><topic>Myoelectricity</topic><topic>Pattern recognition</topic><topic>Signal quality</topic><topic>Speaking</topic><topic>Speech</topic><topic>surface electromyography (sEMG)</topic><topic>Swallowing</topic><topic>total laryngectomy</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>McNulty, Johnny</creatorcontrib><creatorcontrib>de Jager, Kylie</creatorcontrib><creatorcontrib>Lancashire, Henry T.</creatorcontrib><creatorcontrib>Graveston, James</creatorcontrib><creatorcontrib>Birchall, Martin</creatorcontrib><creatorcontrib>Vanhoestenberghe, Anne</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998–Present</collection><collection>IEEE Electronic Library Online</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>IEEE transactions on medical robotics and bionics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>McNulty, Johnny</au><au>de Jager, Kylie</au><au>Lancashire, Henry T.</au><au>Graveston, James</au><au>Birchall, Martin</au><au>Vanhoestenberghe, Anne</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Prediction of Larynx Function Using Multichannel Surface EMG Classification</atitle><jtitle>IEEE transactions on medical robotics and bionics</jtitle><stitle>TMRB</stitle><addtitle>IEEE Trans Med Robot Bionics</addtitle><date>2021-11-01</date><risdate>2021</risdate><volume>3</volume><issue>4</issue><spage>1032</spage><epage>1039</epage><pages>1032-1039</pages><issn>2576-3202</issn><eissn>2576-3202</eissn><abstract>Total laryngectomy (TL) affects critical functions such as swallowing, coughing and speaking. An artificial, bioengineered larynx (ABL), operated via myoelectric signals, may improve quality of life for TL patients. To evaluate the efficacy of using surface electromyography (sEMG) as a control signal to predict instances of swallowing, coughing and speaking, sEMG was recorded from submental, intercostal and diaphragm muscles. The cohort included TL and control participants. Swallowing, coughing, speaking and movement actions were recorded, and a range of classifiers were investigated for prediction of these actions. Our algorithm achieved F1-scores of 76.0 ± 4.4% (swallows), 93.8 ± 2.8% (coughs) and 70.5 ± 5.4% (speech) for controls, and 67.7 ± 4.4% (swallows), 71.0 ± 9.1% (coughs) and 78.0 ± 3.8% (speech) for TLs, using a random forest (RF) classifier. 75.1 ± 6.9% of swallows were detected within 500 ms of onset in the controls, and 63.1 ± 6.1% in TLs. sEMG can be used to predict critical larynx movements, although a viable ABL requires improvements. Results are particularly encouraging as they encompass a TL cohort. An ABL could alleviate many challenges faced by laryngectomees. This study represents a promising step toward realising such a device.</abstract><cop>United States</cop><pub>IEEE</pub><pmid>34901764</pmid><doi>10.1109/TMRB.2021.3122966</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-7244-5864</orcidid><orcidid>https://orcid.org/0000-0002-8428-7752</orcidid><orcidid>https://orcid.org/0000-0002-1377-7439</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Artificial larynx Bioengineering Classifiers coughing Electromyography Larynx Muscles Myoelectricity Pattern recognition Signal quality Speaking Speech surface electromyography (sEMG) Swallowing total laryngectomy |
title | Prediction of Larynx Function Using Multichannel Surface EMG Classification |
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