Inferring position of motor units from high-density surface EMG
(2024) In Scientific Reports 14(1).- Abstract
The spatial distribution of muscle fibre activity is of interest in guiding therapy and assessing recovery of motor function following injuries of the peripheral or central nervous system. This paper presents a new method for stable estimation of motor unit territory centres from high-density surface electromyography (HDsEMG). This completely automatic process applies principal component compression and a rotatable Gaussian surface fit to motor unit action potential (MUAP) distributions to map the spatial distribution of motor unit activity. Each estimated position corresponds to the signal centre of the motor unit territory. Two subjects were used to test the method on forearm muscles, using two different approaches. With the first... (More)
The spatial distribution of muscle fibre activity is of interest in guiding therapy and assessing recovery of motor function following injuries of the peripheral or central nervous system. This paper presents a new method for stable estimation of motor unit territory centres from high-density surface electromyography (HDsEMG). This completely automatic process applies principal component compression and a rotatable Gaussian surface fit to motor unit action potential (MUAP) distributions to map the spatial distribution of motor unit activity. Each estimated position corresponds to the signal centre of the motor unit territory. Two subjects were used to test the method on forearm muscles, using two different approaches. With the first dataset, motor units were identified by decomposition of intramuscular EMG and the centre position of each motor unit territory was estimated from synchronized HDsEMG data. These positions were compared to the positions of the intramuscular fine wire electrodes with depth measured using ultrasound. With the second dataset, decomposition and motor unit localization was done directly on HDsEMG data, during specific muscle contractions. From the first dataset, the mean estimated depth of the motor unit centres were 8.7, 11.6, and 9.1 mm, with standard deviations 0.5, 0.1, and 1.3 mm, and the respective depths of the fine wire electrodes were 8.4, 15.8, and 9.1 mm. The second dataset generated distinct spatial distributions of motor unit activity which were used to identify the regions of different muscles of the forearm, in a 3-dimensional and projected 2-dimensional view. In conclusion, a method is presented which estimates motor unit centre positions from HDsEMG. The study demonstrates the shifting spatial distribution of muscle fibre activity between different efforts, which could be used to assess individual muscles on a motor unit level.
(Less)
- author
- Lundsberg, Jonathan LU ; Björkman, Anders ; Malesevic, Nebojsa LU and Antfolk, Christian LU
- organization
- publishing date
- 2024-12
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Electromyography, Motor unit depth, Motor unit localization, Motor unit spatial distribution
- in
- Scientific Reports
- volume
- 14
- issue
- 1
- article number
- 3858
- publisher
- Nature Publishing Group
- external identifiers
-
- pmid:38360967
- scopus:85185237789
- ISSN
- 2045-2322
- DOI
- 10.1038/s41598-024-54405-1
- language
- English
- LU publication?
- yes
- id
- 6cf2bd4f-1963-42c5-a7c7-f97f8525b85a
- date added to LUP
- 2024-03-14 10:51:11
- date last changed
- 2024-04-25 07:27:24
@article{6cf2bd4f-1963-42c5-a7c7-f97f8525b85a,
abstract = {{<p>The spatial distribution of muscle fibre activity is of interest in guiding therapy and assessing recovery of motor function following injuries of the peripheral or central nervous system. This paper presents a new method for stable estimation of motor unit territory centres from high-density surface electromyography (HDsEMG). This completely automatic process applies principal component compression and a rotatable Gaussian surface fit to motor unit action potential (MUAP) distributions to map the spatial distribution of motor unit activity. Each estimated position corresponds to the signal centre of the motor unit territory. Two subjects were used to test the method on forearm muscles, using two different approaches. With the first dataset, motor units were identified by decomposition of intramuscular EMG and the centre position of each motor unit territory was estimated from synchronized HDsEMG data. These positions were compared to the positions of the intramuscular fine wire electrodes with depth measured using ultrasound. With the second dataset, decomposition and motor unit localization was done directly on HDsEMG data, during specific muscle contractions. From the first dataset, the mean estimated depth of the motor unit centres were 8.7, 11.6, and 9.1 mm, with standard deviations 0.5, 0.1, and 1.3 mm, and the respective depths of the fine wire electrodes were 8.4, 15.8, and 9.1 mm. The second dataset generated distinct spatial distributions of motor unit activity which were used to identify the regions of different muscles of the forearm, in a 3-dimensional and projected 2-dimensional view. In conclusion, a method is presented which estimates motor unit centre positions from HDsEMG. The study demonstrates the shifting spatial distribution of muscle fibre activity between different efforts, which could be used to assess individual muscles on a motor unit level.</p>}},
author = {{Lundsberg, Jonathan and Björkman, Anders and Malesevic, Nebojsa and Antfolk, Christian}},
issn = {{2045-2322}},
keywords = {{Electromyography; Motor unit depth; Motor unit localization; Motor unit spatial distribution}},
language = {{eng}},
number = {{1}},
publisher = {{Nature Publishing Group}},
series = {{Scientific Reports}},
title = {{Inferring position of motor units from high-density surface EMG}},
url = {{http://dx.doi.org/10.1038/s41598-024-54405-1}},
doi = {{10.1038/s41598-024-54405-1}},
volume = {{14}},
year = {{2024}},
}