Fifty Years of Motor Unit Number Estimation
The objective was to use bibliometric analysis to create an infographic of motor unit number estimation methods over the past 50 years. The original method was published in 1971, but secondary and tertiary waves of research using alternative methods occurred in the early 2000s and a decade later. A...
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| Veröffentlicht in: | Canadian journal of neurological sciences 2023-01, Vol.50 (1), p.109-111 |
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| container_end_page | 111 |
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| container_title | Canadian journal of neurological sciences |
| container_volume | 50 |
| creator | Wright, Regan D. Sivak, Allison Abrahão, Agessandro Jones, Kelvin E. |
| description | The objective was to use bibliometric analysis to create an infographic of motor unit number estimation methods over the past 50 years. The original method was published in 1971, but secondary and tertiary waves of research using alternative methods occurred in the early 2000s and a decade later. A metric of influence was used to determine if different methods had clear peaks of use over the past 50 years. While the original method continues to register influence, the MUNIX method introduced in 2004 stands out as the most influential method to estimate the innervation status of skeletal muscles. |
| doi_str_mv | 10.1017/cjn.2021.500 |
| format | Article |
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The original method was published in 1971, but secondary and tertiary waves of research using alternative methods occurred in the early 2000s and a decade later. A metric of influence was used to determine if different methods had clear peaks of use over the past 50 years. While the original method continues to register influence, the MUNIX method introduced in 2004 stands out as the most influential method to estimate the innervation status of skeletal muscles.</description><identifier>ISSN: 0317-1671</identifier><identifier>EISSN: 2057-0155</identifier><identifier>DOI: 10.1017/cjn.2021.500</identifier><identifier>PMID: 35074033</identifier><language>eng</language><publisher>New York, USA: Cambridge University Press</publisher><subject>Bibliometrics ; Brief Communication ; Electromyography ; Electromyography - methods ; Humans ; Motor Neurons - physiology ; Muscle, Skeletal - physiology ; Physiology ; Software ; Statistical analysis ; Statistical methods</subject><ispartof>Canadian journal of neurological sciences, 2023-01, Vol.50 (1), p.109-111</ispartof><rights>The Author(s), 2021. 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While the original method continues to register influence, the MUNIX method introduced in 2004 stands out as the most influential method to estimate the innervation status of skeletal muscles.</description><subject>Bibliometrics</subject><subject>Brief Communication</subject><subject>Electromyography</subject><subject>Electromyography - methods</subject><subject>Humans</subject><subject>Motor Neurons - physiology</subject><subject>Muscle, Skeletal - physiology</subject><subject>Physiology</subject><subject>Software</subject><subject>Statistical analysis</subject><subject>Statistical methods</subject><issn>0317-1671</issn><issn>2057-0155</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNptkEFLwzAUgIMobk5vnqXgRdDWl6RJ2qOMTYWpF3fwFJI2kY610aQ97N-bsakgnnL58r33PoTOMWQYsLitVl1GgOCMARygMQEmUsCMHaIxUCxSzAUeoZMQVgCEM54foxFlIHKgdIyu543tN8mbUT4kziZPrnc-WXZNnzwPrTY-mYW-aVXfuO4UHVm1DuZs_07Qcj57nT6ki5f7x-ndIq1oyfu0sJUuK8tLKG2t8rLEUChqFBeQG8aLygLLdW0qLUhplNXC6CL-ABs3qvOaTtDVzvvh3edgQi_bJlRmvVadcUOQhBPCeZQUEb38g67c4Lu4nSRFEQeWtKCRutlRlXcheGPlh483-Y3EILcRZYwotxFljBjxi7100K2pf-DvahHI9j7Vat_U7-Z37L_GL_cTekA</recordid><startdate>202301</startdate><enddate>202301</enddate><creator>Wright, Regan D.</creator><creator>Sivak, Allison</creator><creator>Abrahão, Agessandro</creator><creator>Jones, Kelvin E.</creator><general>Cambridge University Press</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88G</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>K9.</scope><scope>M0S</scope><scope>M2M</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-1142-2842</orcidid><orcidid>https://orcid.org/0000-0002-8100-9888</orcidid><orcidid>https://orcid.org/0000-0003-4764-7031</orcidid></search><sort><creationdate>202301</creationdate><title>Fifty Years of Motor Unit Number Estimation</title><author>Wright, Regan D. ; 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| fulltext | fulltext |
| identifier | ISSN: 0317-1671 |
| ispartof | Canadian journal of neurological sciences, 2023-01, Vol.50 (1), p.109-111 |
| issn | 0317-1671 2057-0155 |
| language | eng |
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| source | MEDLINE; Cambridge University Press Journals Complete |
| subjects | Bibliometrics Brief Communication Electromyography Electromyography - methods Humans Motor Neurons - physiology Muscle, Skeletal - physiology Physiology Software Statistical analysis Statistical methods |
| title | Fifty Years of Motor Unit Number Estimation |
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