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Sökning: WFRF:(Antfolk Christian) > (2020-2024) > Spatial decompositi...

Spatial decomposition of ultrafast ultrasound images to identify motor unit activity : a comparative study with intramuscular and surface EMG

Rohlén, Robin (författare)
Lund University,Lunds universitet,Avdelningen för Biomedicinsk teknik,Institutionen för biomedicinsk teknik,Institutioner vid LTH,Lunds Tekniska Högskola,LTH profilområde: Teknik för hälsa,LTH profilområden,Department of Biomedical Engineering,Departments at LTH,Faculty of Engineering, LTH,LTH Profile Area: Engineering Health,LTH Profile areas,Faculty of Engineering, LTH
Lubel, Emma (författare)
Department of Bioengineering, Imperial College London, London, UK
Grandi Sgambato, Bruno (författare)
Department of Bioengineering, Imperial College London, London, UK
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Antfolk, Christian (författare)
Lund University,Lunds universitet,Avdelningen för Biomedicinsk teknik,Institutionen för biomedicinsk teknik,Institutioner vid LTH,Lunds Tekniska Högskola,LTH profilområde: Teknik för hälsa,LTH profilområden,Department of Biomedical Engineering,Departments at LTH,Faculty of Engineering, LTH,LTH Profile Area: Engineering Health,LTH Profile areas,Faculty of Engineering, LTH
Farina, Dario (författare)
Department of Bioengineering, Imperial College London, London, UK
visa färre...
 (creator_code:org_t)
Elsevier, 2023
2023
Engelska.
Ingår i: Journal of Electromyography & Kinesiology. - : Elsevier. - 1050-6411 .- 1873-5711.
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • The smallest voluntarily controlled structure of the human body is the motor unit (MU), comprised of a motoneuron and its innervated fibres. MUs have been investigated in neurophysiology research and clinical applications, primarily using electromyographic (EMG) techniques. Nonetheless, EMG (both surface and intramuscular) has a limited detection volume. A recent alternative approach to detect MUs is ultrafast ultrasound (UUS) imaging. The possibility of identifying MU activity from UUS has been shown by blind source separation (BSS) of UUS images, using optimal separation spatial filters. However, this approach has yet to be fully compared with EMG techniques for a large population of unique MU spike trains. Here we identify individual MU activity in UUS images using the BSS method for 401 MU spike trains from eleven participants based on concurrent recordings of either surface or intramuscular EMG from forces up to 30% of the maximum voluntary contraction (MVC) force. We assessed the BSS method’s ability to identify MU spike trains from direct comparison with the EMG-derived spike trains as well as twitch areas and temporal profiles from comparison with the spike-triggered-averaged UUS images when using the EMG-derived spikes as triggers. We found a moderate rate of correctly identified spikes (53.0 ± 16.0%) with respect to the EMG-identified firings. However, the MU twitch areas and temporal profiles could still be identified accurately, including at 30% MVC force. These results suggest that the current BSS methods for UUS can accurately identify the location and average twitch of a large pool of MUs in UUS images, providing potential avenues for studying neuromechanics from a large cross-section of the muscle. On the other hand, more advanced methods are needed to address the convolutive and partly non-linear summation of velocities for recovering the full spike trains.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP  -- Medicinska och farmaceutiska grundvetenskaper -- Fysiologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Basic Medicine -- Physiology (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Medicinteknik -- Medicinsk bildbehandling (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Medical Engineering -- Medical Image Processing (hsv//eng)

Nyckelord

ultrafast ultrasound
electromyography
motor units
spike-triggered averaging
blind source separation

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