1. The efficiency of manual editing of high-density surface electromyogram decomposition depends on the recorded muscle and contraction level but less on the operator’s experienceNina Murks, Jakob Škarabot, Matej Kramberger, Matjaž Divjak, Gašper Sedej, Tamara Valenčič, Christopher D. Connelly, Haydn Thomason, Aleš Holobar, 2025, original scientific article Abstract: We investigated the agreement and accuracy of manual editing of the high-density electromyogram (hdEMG) decomposition results by seven human operators with various experience levels. All operators edited the same automatically decomposed experimental hdEMG from the first dorsal interosseous (FDI), tibialis anterior (TA), vastus lateralis (VL), and biceps brachii (BB) muscles, and synthetic hdEMG from soleus (SO) and BB muscles at 10%, 30%, 50% and 70% of maximum voluntary contraction. On average, operators kept 13.7 ± 7.4 motor units (MUs) after editing and demonstrated relatively large disagreement in the calculated MU pulse trains (normalized root mean square difference) but relatively high agreement in the identified MU discharges. Inter-operator agreement positively correlated with the initial MU Pulse-to-Noise Ratio used as a quality measure of automatic MU identification, and negatively correlated with the muscle contraction level. Operators agreed more on the results of the simulated than experimental hdEMG. Among the experimental muscles tested, the greatest agreement was demonstrated for VL and the lowest for BB. We obtained similar results when comparing editing to the results of the most experienced operator and to ground truth in simulated cases: the greatest precision and sensitivity were demonstrated for VL, and the lowest for BB. The level of the operator’s experience had a significant impact on the editing of synthetic hdEMG and the detection of the first MU discharge, but not on the rate of agreement or editing time of experimental hdEMG.
Keywords: hdEMG, manual editing, decomposition results, human operators, motor unit, človeški operaterji
Published in DKUM: 14.10.2025; Views: 0; Downloads: 4
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2. The effects of spinal manipulation on motor unit behaviorLucien Robinault, Aleš Holobar, Sylvain Crémoux, Usman Rashid, Imran Khan Niazi, Kelly Holt, Jimmy Lauber, Heidi Haavik, 2021, original scientific article Abstract: Over recent years, a growing body of research has highlighted the neural plastic effects of
spinal manipulation on the central nervous system. Recently, it has been shown that spinal manipulation improved outcomes, such as maximum voluntary force and limb joint position sense, reflecting
improved sensorimotor integration and processing. This study aimed to further evaluate how spinal
manipulation can alter neuromuscular activity. High density electromyography (HD sEMG) signals
from the tibialis anterior were recorded and decomposed in order to study motor unit changes in
14 subjects following spinal manipulation or a passive movement control session in a crossover study
design. Participants were asked to produce ankle dorsiflexion at two force levels, 5% and 10% of
maximum voluntary contraction (MVC), following two different patterns of force production (“ramp”
and “ramp and maintain”). A significant decrease in the conduction velocity (p = 0.01) was observed
during the “ramp and maintain” condition at 5% MVC after spinal manipulation. A decrease in
conduction velocity suggests that spinal manipulation alters motor unit recruitment patterns with an
increased recruitment of lower threshold, lower twitch torque motor units.
Keywords: high-density surface electromyography, chiropractic, electromyography decomposition, motor unit
Published in DKUM: 20.06.2025; Views: 0; Downloads: 6
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5. Acute intermittent hypoxia increases maximal motor unit discharge rates in people with chronic incomplete spinal cord injuryGregory E. P. Pearcey, Babak Afsharipour, Aleš Holobar, Milap S. Sandhu, William Zev Rymer, 2024, original scientific article Abstract: Acute intermittent hypoxia (AIH) is an emerging technique for enhancing neuroplasticity and motor function in respiratory and limb musculature. Thus far, AIH-induced improvements in strength have been reported for upper and lower limb muscles after chronic incomplete cervical spinal cord injury (iSCI), but the underlying mechanisms have been elusive. We used high-density surface EMG (HDsEMG) to determine if motor unit discharge behaviour is altered after 15 × 60 s exposures to 9% inspired oxygen, interspersed with 21% inspired oxygen (AIH), compared to breathing only 21% air (SHAM). We recorded HDsEMG from the biceps and triceps brachii of seven individuals with iSCI during maximal elbow flexion and extension contractions, and motor unit spike trains were identified using convolutive blind source separation. After AIH, elbow flexion and extension torque increased by 54% and 59% from baseline (P = 0.003), respectively, whereas there was no change after SHAM. Across muscles, motor unit discharge rates increased by ∼4 pulses per second (P = 0.002) during maximal efforts, from before to after AIH. These results suggest that excitability and/or activation of spinal motoneurons is augmented after AIH, providing a mechanism to explain AIH-induced increases in voluntary strength. Pending validation, AIH may be helpful in conjunction with other therapies to enhance rehabilitation outcomes after incomplete spinal cord injury, due to these enhancements in motor unit function and strength.
Keywords: muscle strength, motoneuron function, motor unit
Published in DKUM: 02.08.2024; Views: 73; Downloads: 35
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6. Motor unit identification in the M waves recorded by high-density electromyMiloš Kalc, Jakob Škarabot, Matjaž Divjak, Filip Urh, Matej Kramberger, Matjaž Vogrin, Aleš Holobar, 2023, original scientific article Keywords: M wave, high-density surface EMG, firing identification, motor unit
Published in DKUM: 13.06.2024; Views: 144; Downloads: 19
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7. Materials for HybridNeuro webinar titled "Validation of results: statistical models and MU identification accuracy"Aleš Holobar, Nina Murks, 2024, complete scientific database of research data Abstract: This dataset contains a collection of teaching materials that were used in the HybridNeuro project webinar titled "Validation of results: statistical models and MU identification accuracy". The webinar was presented by Aleš Holobar and covered the complexities of motor unit (MU) identification accuracy, regression analysis and Bayesian models. The primary aim of the webinar was to spark a robust discussion within the scientific community, particularly focusing on the application and implications of linear mixed models and Bayesian regression in the realm of MU identification. The teaching materials include Matlab and R source code for statistical analysis of the included data, as well as three examples of MU identification results in CSV format (from both synthetic and experimental HDEMG signals). The presentation slides in PDF format are also included. The dataset is approximately 9 MB in size.
Keywords: HybridNeuro, webinar, teaching materials, statistical models, regression analysis, motor unit identification, matlab, rstudio, statistics, surface high density electromyogram (HDEMG), tibialis anterior, dataset
Published in DKUM: 30.05.2024; Views: 221; Downloads: 37
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8. Simulated and experimental HDEMG signals of biceps brachii muscle for analysis of motor unit mergingAleš Holobar, Jakob Škarabot, Dario Farina, 2024, complete scientific database of research data Abstract: This dataset contains a collection of simulated and experimental surface HDEMG recordings of the biceps brachii muscle during the isometric elbow flexion. Simulated data contains 50 recordings: 5 subjects and 5 excitation levels, each with and without added noise. Experimental data contains 16 recordings: 2 subjects with 4 excitation levels and 2 repetitions of each level. Synthetic data was simulated using the cylindrical volume conductor model [1] and the motor unit recruitment and firing modulation model proposed in [2]. Each recording is 20 seconds in length with 90 HDEMG channels sampled at 2048 Hz and is stored as a 2D matrix of raw EMG values in Matlab’s MAT format. Experimental surface EMG data was recorded on two volunteers during isometric contractions at constant force level. Each recording is 25 seconds in length with 64 HDEMG channels sampled at 2048 Hz and is also stored as a 2D matrix of raw EMG values in Matlab’s MAT format. The dataset is approximately 1.5 GB in size.
Keywords: surface high density electromyogram (HDEMG), motor unit, spike train, motor unit merging, simulated data, experimental data, biceps brachii, dataset
Published in DKUM: 30.05.2024; Views: 172; Downloads: 34
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