1. Hybrid neuroscience based on cerebral and muscular information for motor rehabilitation and neuromuscular disorders : D3.1 Established measurement protocol with prepared instrumentationMatej Kramberger, Nina Murks, Matjaž Divjak, Silvia Muceli, Alejandro Pascual Valdunciel, Monica Marlene Rojas Martinez, Miquel Angel Mañanas, Božidar Potočnik, 2023, final research report Published in DKUM: 19.05.2025; Views: 0; Downloads: 2
 Full text (982,44 KB)
This document has many files! More... |
2. Tutorial on editing the decomposition results from isometric contractionsNina Murks, Jakob Škarabot, Aleš Holobar, 2025, dictionary, encyclopaedia, lexicon, manual, atlas, map Abstract: This tutorial focuses on editing decomposition results from high-density electromyograms. It covers the most common scenarios that may arise during the editing process and demonstrates how to resolve them using the CKC Inspector in the Demuse tool.
Keywords: Editing, decomposisition results, dhEMG, Demuse, CKC inspector
Published in DKUM: 12.02.2025; Views: 0; Downloads: 66
Full text (1,82 MB) |
3. 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: 25
Full text (108,35 KB)
This document has many files! More... |
4. Decoding firings of a large population of human motor units from high-density surface electromyogram in response to transcranial magnetic stimulationJakob Škarabot, Claudia Ammann, Thomas G. Balshaw, Matjaž Divjak, Filip Urh, Nina Murks, Guglielmo Foffani, Aleš Holobar, 2023, original scientific article Abstract: We describe a novel application of methodology for high-density surface electromyography (HDsEMG) decomposition to identify motor unit (MU) firings in response to transcranial magnetic stimulation (TMS). The method is based on the MU filter estimation from HDsEMG decomposition with convolution kernel compensation during voluntary isometric contractions and its application to contractions elicited by TMS. First, we simulated synthetic HDsEMG signals during voluntary contractions followed by simulated motor evoked potentials (MEPs) recruiting an increasing proportion of the motor pool. The estimation of MU filters from voluntary contractions and their application to elicited contractions resulted in high (>90%) precision and sensitivity of MU firings during MEPs. Subsequently, we conducted three experiments in humans. From HDsEMG recordings in first dorsal interosseous and tibialis anterior muscles, we demonstrated an increase in the number of identified MUs during MEPs evoked with increasing stimulation intensity, low variability in the MU firing latency and a proportion of MEP energy accounted for by decomposition similar to voluntary contractions. A negative relationship between the MU recruitment threshold and the number of identified MU firings was exhibited during the MEP recruitment curve, suggesting orderly MU recruitment. During isometric dorsiflexion we also showed a negative association between voluntary MU firing rate and the number of firings of the identified MUs during MEPs, suggesting a decrease in the probability of MU firing during MEPs with increased background MU firing rate. We demonstrate accurate identification of a large population of MU firings in a broad recruitment range in response to TMS via non-invasive HDsEMG recordings. KEY POINTS: Transcranial magnetic stimulation (TMS) of the scalp produces multiple descending volleys, exciting motor pools in a diffuse manner. The characteristics of a motor pool response to TMS have been previously investigated with intramuscular electromyography (EMG), but this is limited in its capacity to detect many motor units (MUs) that constitute a motor evoked potential (MEP) in response to TMS. By simulating synthetic signals with known MU firing patterns, and recording high-density EMG signals from two human muscles, we show the feasibility of identifying firings of many MUs that comprise a MEP. We demonstrate the identification of firings of a large population of MUs in the broad recruitment range, up to maximal MEP amplitude, with fewer required stimuli compared to intramuscular EMG recordings. The methodology demonstrates an emerging possibility to study responses to TMS on a level of individual MUs in a non-invasive manner.
Keywords: transcranial magnetic stimulation, TMS, electromyiograms
Published in DKUM: 10.04.2024; Views: 421; Downloads: 22
Full text (3,57 MB)
This document has many files! More... |
5. Inter-person differences in isometric coactivations of triceps surae and tibialis anterior decrease in young, but not in older adults after 14 days of bed restMatjaž Divjak, Gašper Sedej, Nina Murks, Mitja Gerževič, Uroš Marušič, Rado Pišot, Boštjan Šimunič, Aleš Holobar, 2022, original scientific article Abstract: We examined activation patterns of the gastrocnemius medialis (GM), gastrocnemius lateralis (GL), soleus (SO), and tibialis anterior (TA) muscles in eight older (58.4 ± 3.3 years) and seven young (23.1 ± 2.9 years) participants, before and after 14 days of horizontal bed rest. Visual feedback on the exerted muscle torque was provided to the participants. The discharge patterns of individual motor units (MUs) were studied in three repetitions of isometric plantar flexion at 30 and 60% of Maximum Voluntary Contraction (MVC), before, and 1 day after the 14-day bed rest, respectively. In the GL and GM muscles, the older participants demonstrated higher MU discharge rates than the young, regardless of the contraction level, both before and after the bed rest. In the TA and SO muscles, the differences between the older and young participants were less consistent. Detailed analysis revealed person-specific changes in the MU discharge rates after the bed rest. To quantify the coactivation patterns we calculated the correlation coefficients between the cumulative spike trains of identified MUs from each muscle, and measured the root mean square difference of the correlation coefficients between the trials of the same session (intra-session variability) and between different sessions (inter-session variability) in each participant (intra-person comparison) and across participants (inter-person comparison). In the intra-person comparison, the inter-session variability was higher than the intra-session variability, either before or after the bed rest. At 60% MVC torque, the young demonstrated higher inter-person variability of coactivation than the older participants, but this variability decreased significantly after the bed rest. In older participants, inter-person variability was consistently lower at 60% than at 30% MVC torque. In young participants, inter-person variability became lower at 60% than at 30% MVC torque only after the bed rest. Precaution is required when analyzing the MU discharge and coactivation patterns, as individual persons demonstrate individual adaptations to aging or bed rest.
Keywords: mišičnoskeletni sistem, mišice, bed rest, staranje, elektromiografija, high density electromyography, muscle disuse, motor units, discharge rate, aging
Published in DKUM: 07.07.2023; Views: 539; Downloads: 61
Full text (4,31 MB)
This document has many files! More... |
6. Sistem za beleženje zgodovine ročnega urejanja rezultatov dekompozicije večkanalnih površinskih elektromiogramov : diplomsko deloNina Murks, 2022, master's thesis Abstract: Namen magisterska dela je izdelati sistem za shranjevanje zgodovine ročnega urejanja rezultatov dekompozicije večkanalnih površinskih elektromiogramov ter prikaz njegove uporabe. Področje obsega predstavljene strategije urejanja rezultatov dekompozicije, opis delovanja ter implementacije sistema za shranjevanje zgodovine in njegovo uporabo. Prva predstavljena uporaba sistema za beleženje zgodovine je izračun in prikaz statistike urejanja, s pomočjo katere je možno vrednotiti strategije urejanja. Drugi primer uporabe sistema za beleženje zgodovine je preprost primer delne avtomatizacije urejanja, pri čemer sta uporabljena dva različna modela nevronskih mrež. Prvi model vsebuje konvolucijske sloje, drugi pa sloje LSTM. Preučili smo uspešnost obeh modelov ter prikazali njune rezultate. Model s konvolucijskimi sloji je dosegel 71-% preciznost ob 83-% priklicu napovedi urejanja, model s sloji LSTM pa 100-% preciznost ob 75-% priklicu.
Keywords: beleženje zgodovine, rezultati dekompozicije, statistika urejanja, delna avtomatizacija urejanja
Published in DKUM: 14.06.2022; Views: 951; Downloads: 152
Full text (5,33 MB) |
7. Vizualizacija in podpora matematičnim izrazom v produktu Dewesoft : diplomsko deloNina Murks, 2020, undergraduate thesis Abstract: V okviru diplomskega dela smo izdelali kontrolo matematičnega urejevalnika za produkt Dewesoft. Ta omogoča številne funkcionalnosti, ki olajšajo delo z matematičnimi izrazi, saj ti hitro postanejo kompleksni – posledično je delo z njimi oteženo. Izdelali smo kontrolo, ki omogoča lažje pisanje izrazov, njihovo popravljanje in vizualizacijo. Pri implementaciji smo uporabili knjižnico SynEdit ter jezika Delphi in C++. Kontrolo urejevalnika smo nazadnje vključili tudi v knjižnico MUI, ki omogoča uporabo kontrole znotraj produkta Dewesoft.
Keywords: kontrola, matematični urejevalnik, Dewesoft, SynEdit, MUI
Published in DKUM: 03.11.2020; Views: 820; Downloads: 200
Full text (1,42 MB) |
