Estimating motor unit discharge patterns from high-density surface electromyogram.
Open accessAbstract
Objective We systematically tested the capability of the Convolution Kernel Compensation (CKC) method to identify motor unit (MU) discharge patterns from the simulated and experimental surface electromyogram (sEMG) during low-force contractions.Methods sEMG was detected with a grid of 13 x 5 electrodes. In simulated signals with 20 dB signal-to-noise ratio, 11+/-3 out of 63 concurrently active MUs were identified with sensitivity >95% in the estimation of their discharge times. In experimental signals recorded at 0-10% of the maximal force, the discharge patterns of (range) 11-19 MUs (abductor pollicis; n=8 subjects), 9-17 MUs (biceps brachii; n=2), 7-11 MUs (upper trapezius; n=2), and 6-10 MUs (vastus lateralis; n=2) were identified. In the abductor digiti minimi muscle of one subject, the decomposition results from concurrently recorded sEMG and intramuscular EMG (iEMG) were compared; the two approaches agreed on 98+/-1% of MU discharges.Conclusion It is possible to identify the discharge patterns of several MUs during low-force contractions from high-density sEMG.Significance sEMG can be used for the analysis of individual MUs when the application of needles is not desirable or in combination with iEMG to increase the number of sampled MUs.
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The motor unit decomposition procedure was previously extensively validated on signals from various skeletal muscles.
“We followed the decomposition procedure that was previously extensively validated on signals from various skeletal muscles (7,17,21,25–28).”
From Modulation of Neural and Muscular Adaptation Processes During Resistance Training by Fish Protein Ingestions in Older Adults (2020) · cites this paper as [21]
Discharges with interdischarge intervals < 33.3 or >250 ms were excluded because firing rates calculated from this range are unusually high (>30 Hz) or low (<4 Hz) for the VL muscle.
“We excluded the discharges with interdischarge intervals < 33.3 or >250 ms because firing rates that calculated from this range of interdischarge intervals are unusually high (>30 Hz) or low (<4 Hz) for the VL muscle (7,20,21,30,31).”
From Modulation of Neural and Muscular Adaptation Processes During Resistance Training by Fish Protein Ingestions in Older Adults (2020) · cites this paper as [21]
The multi-channel surface EMG technique facilitates robust assessment of motor unit firing rates along with their recruitment thresholds.
“Moreover, the multi-channel surface EMG technique facilitates the robust assessment of motor unit firing rates along with their recruitment thresholds (Holobar et al., 2009).”
From Effect of resistance training and fish protein intake on motor unit firing pattern and motor function of elderly (2018) · cites this paper as Holobar et al., 2009
Cites
Independent Component Analysis
Hyvärinen, A., Hoyer, P. O., & Inki, M. (2004) · The MIT Press eBooks · doi:10.7551/mitpress/3717.003.0014 · Cited by 7,938 · see citing works
Independent Component Analysis
(2001) · Cambridge University Press eBooks · doi:10.1017/cbo9780511624148 · Cited by 1,949 · see citing works
Relation between size of neurons and their susceptibility to discharge
Henneman, E. (1957) · Science · doi:10.1126/science.126.3287.1345 · Cited by 1,227 · see citing works
(2004) · Wiley eBooks · doi:10.1002/0471678384 · Cited by 1,165 · see citing works
Models of recruitment and rate coding organization in motor-unit pools.
Fuglevand, A. J., Winter, D. A., & Patla, A. E. (1993) · Journal of Neurophysiology · doi:10.1152/jn.1993.70.6.2470 · Cited by 988 · cited 5× · see citing works
“The discharge rates at the force peak (10% MVC) were significantly larger than at recruitment and derecruitment and were inversely correlated to recruitment threshold (De Luca et al., 1982; Fuglevand et al., 1993; Hogrel, 2003; Monster and Chan, 1977).”
BackgroundMethodResultInfluentialBehaviour of human motor units in different muscles during linearly varying contractions
de Luca, C. J., LeFever, R. S., McCue, M. P., & Xenakis, A. P. (1982) · The Journal of Physiology · doi:10.1113/jphysiol.1982.sp014293 · Cited by 719 · see citing works
Multichannel Blind Source Separation Using Convolution Kernel Compensation
Holobar, A., & Zazula, D. (2007) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2007.896108 · Cited by 651 · see citing works
Self-citationDecomposition of Surface EMG Signals
Luca, C. J. D., Adam, A., Wotiz, R. P., Gilmore, L., & Nawab, S. H. (2006) · Journal of Neurophysiology · doi:10.1152/jn.00009.2006 · Cited by 513 · see citing works
Influence of amplitude cancellation on the simulated surface electromyogram
Keenan, K. G., Farina, D., Maluf, K. S., Merletti, R., & Enoka, R. M. (2004) · Journal of Applied Physiology · doi:10.1152/japplphysiol.00894.2004 · Cited by 386 · see citing works
Self-citationElectromyography: Physiology, Engineering and Non-Invasive Applications
Madhavan, G. (2005) · Annals of Biomedical Engineering · doi:10.1007/s10439-005-8160-y · Cited by 367 · see citing works
Andreassen, S., & Arendt‐Nielsen, L. (1987) · The Journal of Physiology · doi:10.1113/jphysiol.1987.sp016756 · Cited by 352 · see citing works
Analysis of motor units with high-density surface electromyography
Merletti, R., Holobar, A., & Farina, D. (2008) · Journal of Electromyography and Kinesiology · doi:10.1016/j.jelekin.2008.09.002 · Cited by 351 · see citing works
Self-citationMerletti, R., Botter, A., Troiano, A., Merlo, E., & Minetto, M. A. (2008) · Clinical Biomechanics · doi:10.1016/j.clinbiomech.2008.08.006 · Cited by 345 · see citing works
Self-citationIsometric force production by motor units of extensor digitorum communis muscle in man
Monster, A. W., & Chan, H. (1977) · Journal of Neurophysiology · doi:10.1152/jn.1977.40.6.1432 · Cited by 320 · see citing works
Propagation velocity in human muscle fibers in situ.
Stålberg, E. (1966) · PubMed · Cited by 320 · see citing works
EMGLAB: An interactive EMG decomposition program
McGill, K. C., Lateva, Z. C., & Marateb, H. R. (2005) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2005.05.015 · Cited by 312 · see citing works
A novel approach for precise simulation of the EMG signal detected by surface electrodes
Farina, D., & Merletti, R. (2001) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.923782 · Cited by 283 · see citing works
Self-citationCompartmentalization of motor units in the cat neck muscle, biventer cervicis
Armstrong, J. B., Rose, P. K., Vanner, S., Bakker, G. J., & RICHMOND, F. J. R. (1988) · Journal of Neurophysiology · doi:10.1152/jn.1988.60.1.30 · Cited by 276 · see citing works
EMG signal decomposition: how can it be accomplished and used?
Stashuk, D. W. (2001) · Journal of Electromyography and Kinesiology · doi:10.1016/s1050-6411(00)00050-x · Cited by 269 · see citing works
Macro EMG, a new recording technique.
Stålberg, E. (1980) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp.43.6.475 · Cited by 238 · see citing works
Farina, D., Muhammad, W., Fortunato, E., et al. (2001) · Medical & Biological Engineering & Computing · doi:10.1007/bf02344807 · Cited by 184 · see citing works
Self-citationGazzoni, M., Farina, D., & Merletti, R. (2004) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2004.01.002 · Cited by 180 · see citing works
Self-citationElectrophysiological cross section of the motor unit.
Stålberg, E., & Antoni, L. (1980) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp.43.6.469 · Cited by 179 · see citing works
Correlation-based decomposition of surface electromyograms at low contraction forces
Holobar, A., & Zazula, D. (2004) · Medical & Biological Engineering & Computing · doi:10.1007/bf02350989 · Cited by 167 · see citing works
Self-citationNoninvasive estimation of motor unit conduction velocity distribution using linear electrode arrays
Farina, D., Fortunato, E., & Merletti, R. (2000) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.827303 · Cited by 156 · see citing works
Self-citationDetecting the Unique Representation of Motor-Unit Action Potentials in the Surface Electromyogram
Farina, D., Negro, F., Gazzoni, M., & Enoka, R. M. (2008) · Journal of Neurophysiology · doi:10.1152/jn.90219.2008 · Cited by 150 · see citing works
Self-citationUsing two-dimensional spatial information in decomposition of surface EMG signals
Kleine, B. U., van Dijk, J. P., Lapatki, B. G., Zwarts, M. J., & Stegeman, D. F. (2006) · Journal of Electromyography and Kinesiology · doi:10.1016/j.jelekin.2006.05.003 · Cited by 140 · see citing works
Amplitude cancellation reduces the size of motor unit potentials averaged from the surface EMG
Keenan, K. G., Farina, D., Merletti, R., et al. (2006) · Journal of Applied Physiology · doi:10.1152/japplphysiol.01282.2005 · Cited by 129 · see citing works
Self-citationOVERUSE SYNDROME: A MUSCLE BIOPSY STUDY
Dennett, X., & Fry, H. H. (1988) · The Lancet · doi:10.1016/s0140-6736(88)91714-x · Cited by 123 · see citing works
Doherty, T. J., & Stashuk, D. W. (2003) · Muscle & Nerve · doi:10.1002/mus.10427 · Cited by 122 · see citing works
Blok, J. H., van Dijk, J. P., Drost, G., Zwarts, M. J., & Stegeman, D. F. (2002) · Review of Scientific Instruments · doi:10.1063/1.1455134 · Cited by 116 · see citing works
Nakamura, H., Yoshida, M., Kotani, M., et al. (2004) · Journal of Electromyography and Kinesiology · doi:10.1016/j.jelekin.2004.01.004 · Cited by 106 · see citing works
Mitochondrial dysfunction and neuromuscular disease
Nardin, R. A., & Johns, D. R. (2001) · Muscle & Nerve · doi:10.1002/1097-4598(200102)24:2 · Cited by 100 · see citing works
Decomposition of indwelling EMG signals
Nawab, S. H., Wotiz, R. P., & Luca, C. J. D. (2008) · Journal of Applied Physiology · doi:10.1152/japplphysiol.00170.2007 · Cited by 86 · see citing works
Motor unit recruitment pattern during low‐level static and dynamic contractions
Søgaard, K. (1995) · Muscle & Nerve · doi:10.1002/mus.880180305 · Cited by 75 · see citing works
Automatic decomposition electromyography (ADEMG): validation and normative data in brachial biceps
McGill, K. C., & Dorfman, L. J. (1985) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/0013-4694(85)91038-7 · Cited by 59 · see citing works
Use of surface EMG for studying motor unit recruitment during isometric linear force ramp
Hogrel, J. (2003) · Journal of Electromyography and Kinesiology · doi:10.1016/s1050-6411(03)00026-9 · Cited by 59 · see citing works
A decomposition algorithm for surface electrode-array electromyogram
García, G. A., Okuno, R., & Azakawa, K. (2005) · IEEE Engineering in Medicine and Biology Magazine · doi:10.1109/memb.2005.1463398 · Cited by 50 · see citing works
Farina, D., Gazzoni, M., & Camelia, F. (2004) · Journal of Applied Physiology · doi:10.1152/japplphysiol.01047.2003 · Cited by 45 · see citing works
Self-citationParameters of human motor unit twitches obtained by intramuscular microstimulation
Elek, J., Kossev, A. R., Dengler, R., et al. (1992) · Neuromuscular Disorders · doi:10.1016/0960-8966(92)90058-e · Cited by 39 · see citing works
Decomposition and Analysis of Intramuscular Electromyographic Signals
Luca, C. J. D., & Adam, A. (1999) · Springer eBooks · doi:10.1007/978-3-642-58552-4_27 · Cited by 38 · see citing works
An approach to surface EMG decomposition based on higher-order cumulants
Zazula, D., & Holobar, A. (2005) · Computer Methods and Programs in Biomedicine · doi:10.1016/s0169-2607(05)80006-9 · Cited by 34 · see citing works
Self-citationReinnervation of motor units in intrinsic muscles of a transplanted hand
Lanzettà, M., Pozzo, M., Bottin, A., et al. (2004) · Neuroscience Letters · doi:10.1016/j.neulet.2004.10.001 · Cited by 32 · see citing works
Motor unit recruitment pattern during low level static and dynamic contractions
Gaard, K. S. (1995) · Muscle & Nerve · Cited by 10 · see citing works
Discharge Variability of Motor Units in an Intrinsic Muscle of Transplanted Hand
Farina, D., Pozzo, M., Lanzettà, M., et al. (2008) · Journal of Neurophysiology · doi:10.1152/jn.01273.2007 · Cited by 8 · see citing works
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Heckman, C. J., & Enoka, R. M. (2012) · Comprehensive Physiology · doi:10.1002/cphy.c100087 · Cited by 414 · see citing works
De Luca, C. J., & Hostage, E. C. (2010) · Journal of Neurophysiology · doi:10.1152/jn.01018.2009 · Cited by 326 · see citing works
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“3 or >250 ms because firing rates that calculated from this range of interdischarge intervals are unusually high (>30 Hz) or low (<4 Hz) for the VL muscle (7,20,21,30,31).”
BackgroundSelf-citation
- Authors
- Holobar, A., Farina, D., Gazzoni, M., Merletti, R., & Zazula, D.
- Affiliations
- University of Maribor (SI)
- Aalborg University (DK)
- Politecnico di Torino (IT)
- Venue
- Clinical Neurophysiology
- Publisher
- Elsevier BV
- Published
- 2009-03
- Volume
- 120
- Issue
- 3
- Pages
- 551-562
- ISSN
- 1388-2457 (ISSN-L)
- OpenAlex
- W1964919144
- Cited by
- 318
- References
- 45
- Citations by year
- 2026: 12 · 2025: 30 · 2024: 34 · 2023: 30 · 2022: 27 · 2021: 28 · 2020: 22 · 2019: 23 · 2018: 14 · 2017: 11 · 2016: 13 · 2015: 15 · 2014: 15 · 2013: 11 · 2012: 10
- FWCI
- 6.41
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- Locations
- Clinical Neurophysiology (publishedVersion)
- PubMed (publishedVersion)
- PORTO@Iris (submittedVersion, other-oa)
- PORTO Publications Open Repository TOrino (Politecnico di Torino) (submittedVersion)
- VBN Forskningsportal (Aalborg Universitet) (submittedVersion)
- Funders
- Compagnia di San Paolo
- Teknologi og Produktion, Det Frie Forskningsråd
- European Space Agency
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Muscle activation and electromyography studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Peripheral Nerve Disorders
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Muscle Physiology and Disorders
- Keywords
- motor unit firing patterns, high-density surface electromyography, motor unit decomposition, intramuscular electromyography, biceps brachii, upper trapezius, vastus lateralis, abductor digiti minimi, signal-to-noise ratio
- MeSH terms
- Action Potentials, Adult, Arm, Computer Simulation, Electrodes, Electromyography, Hand, Humans, Male, Motor Neurons, Muscle Contraction, Neuromuscular Junction, Shoulder, Signal Processing, Computer-Assisted, Thigh, Muscle, Skeletal, Muscle Fibers, Skeletal, Quadriceps Muscle
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