Computer-Based Algorithmic Determination of Muscle Movement Onset Using M-Mode Ultrasonography.
The study purpose was to evaluate the use of computer-automated algorithms as a replacement for subjective, visual determination of muscle contraction onset using M-mode ultrasonography. Biceps and quadriceps contraction images were analyzed visually and with three different classes of algorithms: p...
| Publicado en: | Ultrasound in Medicine & Biology Vol. 43; no. 5; pp. 1070 - 1076 |
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| Autores principales: | , , |
| Formato: | research Journal Article |
| Publicado: |
Elsevier B.V.
May2017
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=122371993&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 122371993 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 03015629 JJ6 jtl: Ultrasound in Medicine & Biology issn: 03015629 maglogo: N pubinfo: dt: May2017 vid: 43 iid: 5 pid: 467 pub: Elsevier B.V. place: New York, New York artinfo: ui: 122371993 122371993 NLM28236534 122371993 10.1016/j.ultrasmedbio.2016.12.019 NLM28236534 122371993 ppf: 1070 ppct: 6 formats: tig: atl: Computer-Based Algorithmic Determination of Muscle Movement Onset Using M-Mode Ultrasonography. aug: au: Tweedell, Andrew J. Haynes, Courtney A. Tenan, Matthew S. affil: U.S. Army Research Laboratory, Human Research & Engineering Directorate, Aberdeen Proving Ground, Maryland, USA sug: subj: Ultrasonography Methods Muscle, Skeletal Muscle Contraction Physiology Image Processing, Computer Assisted Methods Signal Processing, Computer Assisted Female Young Adult Movement Electromyography Methods Middle Age Male Algorithms Adult Human Middle Aged: 45-64 years Adult: 19-44 years Female Male ab: The study purpose was to evaluate the use of computer-automated algorithms as a replacement for subjective, visual determination of muscle contraction onset using M-mode ultrasonography. Biceps and quadriceps contraction images were analyzed visually and with three different classes of algorithms: pixel standard deviation (SD), high-pass filter and Teager Kaiser energy operator transformation. Algorithmic parameters and muscle onset threshold criteria were systematically varied within each class of algorithm. Linear relationships and agreements between computed and visual muscle onset were calculated. The top algorithms were high-pass filtered with a 30 Hz cutoff frequency and 20 SD above baseline, Teager Kaiser energy operator transformation with a 1200 absolute SD above baseline and SD at 10% pixel deviation with intra-class correlation coefficients (mean difference) of 0.74 (37.7 ms), 0.80 (61.8 ms) and 0.72 (109.8 ms), respectively. The results suggest that computer automated determination using high-pass filtering is a potential objective alternative to visual determination in human movement science. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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