Umeå University's logo

umu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Quantifying the spatial distribution of individual muscle units using high-density surface EMG and ultrafast ultrasound
Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.ORCID iD: 0000-0003-4328-5467
Politecnico di Torino, Italy.
Politecnico di Torino, Italy.
Umeå University, Faculty of Medicine, Department of Radiation Sciences.ORCID iD: 0000-0003-4288-1208
Show others and affiliations
2023 (English)In: ECSS Paris 2023 Oral presentations: Biomechanics & Motor control / [ed] Jakob Škarabot; Julian Alcazar, 2023, article id 2493Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

INTRODUCTION:Resistance training is a well-known intervention to improve muscle strength (1), with motor unit (MU) adaptation playing an important role (2). Recently, MUs were tracked in humans before and after resistance training using high-density surface electromyography (HDsEMG), showing a correlation between maximal force increase and MUs’ average discharge rate (3). Although these results demonstrate the relationship between an increase in strength and MU activity, only MU-level neural adaptation was considered. Indeed, neural and muscular information needs to be studied jointly to understand the exact adaptations of the MUs in response to resistance training (4).Recently, a method based on ultrafast ultrasound was presented, providing estimates of MU territories in cross-section and the train of twitches evoked by the spinal motoneurons’ discharges (5). In this study, as a proof-of-concept, we combined ultrafast ultrasound and HDsEMG to explore the spatial distribution of individual MUs.

METHODS:In a cross-sectional study, four participants performed low-force isometric contractions of the biceps brachii muscle while recording HDsEMG and ultrafast ultrasound signals from the biceps brachii muscle.The HDsEMG signals were decomposed into individual MU discharge timings (6), and the ultrafast ultrasound signals were decomposed into many components, each having a spatial map and temporal signal (5). We matched each discharge timing of a MU with a component based on spike-triggered averaging of the component’s temporal signal. Given a selected component, we applied a threshold to the spatial map and calculated the centroid and an equivalent diameter.

RESULTS:Out of 16 recordings from four subjects, we decomposed 82 MUs from HDsEMG. Given this, we found 32 matches between individual MU discharges and ultrasound components where the triggered twitches had a significant amplitude. The estimated territories were 4.6 ± 1.1 mm (ranging from 2.8 to 8.6 mm), in line with findings from previous research using scanning-EMG (7). Moreover, the components were located 12.7 ± 3.4 mm below the skin (ranging from 6.4 to 19.4 mm).

CONCLUSION:Our results show that using ultrafast ultrasound and HDsEMG in a strength training intervention, we should be able to quantify the relative contribution of the nervous system and skeletal muscle at the MU level. This information may provide the time course of both neural and hypertrophic adaptations to resistance training and elucidate the relative contributions of each to strength gain.

Place, publisher, year, edition, pages
2023. article id 2493
National Category
Physiology Medical Image Processing
Identifiers
URN: urn:nbn:se:umu:diva-211508OAI: oai:DiVA.org:umu-211508DiVA, id: diva2:1781510
Conference
ECSS Paris 2023, The 28th Annual Congress of the European College of Sport Science, Paris, France, July 4-7, 2023
Funder
Wenner-Gren Foundations, RSh2022-0028Swedish National Centre for Research in Sports, D2023-0003
Note

Session-ID: OP-BM20

Available from: 2023-07-10 Created: 2023-07-10 Last updated: 2023-07-10Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Abstract

Authority records

Rohlén, RobinGrönlund, Christer

Search in DiVA

By author/editor
Rohlén, RobinGrönlund, Christer
By organisation
Radiation PhysicsDepartment of Radiation Sciences
PhysiologyMedical Image Processing

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 292 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf