Open Access
EMG filling analysis, a new method for the assessment of recruitment of motor units with needle EMG
(Elsevier, 2025-02-20) Mariscal Aguilar, Cristina; Navallas Irujo, Javier; Malanda Trigueros, Armando; Recalde Villamayor, Silvia; Rodríguez Falces, Javier; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza; Institute of Smart Cities - ISC
Objectives: The progression of recruitment of motor unit potentials (MUPs) during increasing voluntary contraction can provide important information about the motor units (MUs) innervating a muscle. Here, we described a method to quantitate the recruitment level of the intramuscular electromyographic (iEMG) signal during an increasing force level. Methods: Concentric needle EMG signals were recorded from the tibialis anterior of healthy subjects as force was gradually increased from 0 to maximum force. The iEMG filling process was analyzed by measuring the EMG filling factor (FF), calculated from the mean rectified iEMG and the root mean square iEMG. Results: (1) The iEMG activity at low contraction forces was “discrete” (FF<0.3) for all participants. (2) The iEMG activity at maximal effort was “full” (FF>0.5) for 83 % of the participants, whereas it was “incompletely-reduced” (0.3
Open Access
M-wave changes caused by brief voluntary and stimulated isometric contractions
(Springer, 2023) Rodríguez Falces, Javier; Malanda Trigueros, Armando; Navallas Irujo, Javier; Place, Nicolas; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
Introduction Under isometric conditions, the increase in muscle force is accompanied by a reduction in the fbers’ length. The efects of muscle shortening on the compound muscle action potential (M wave) have so far been investigated only by computer simulation. This study was undertaken to assess experimentally the M-wave changes caused by brief voluntary and stimulated isometric contractions. Methods Two diferent methods of inducing muscle shortening under isometric condition were adopted: (1) applying a brief (1 s) tetanic contraction and (2) performing brief voluntary contractions of diferent intensities. In both methods, supramaximal stimulation was applied to the brachial plexus and femoral nerves to evoke M waves. In the frst method, electrical stimulation (20 Hz) was delivered with the muscle at rest, whereas in the second, stimulation was applied while participants performed 5-s stepwise isometric contractions at 10, 20, 30, 40, 50, 60, 70, and 100% MVC. The amplitude and duration of the frst and second M-wave phases were computed. Results The main fndings were: (1) on application of tetanic stimulation, the amplitude of the M-wave frst phase decreased (~10%, P<0.05), that of the second phase increased (~50%, P<0.05), and the M-wave duration decreased (~20%, P<0.05) across the frst fve M waves of the tetanic train and then plateaued for the subsequent responses; (2) when superimposing a single electrical stimulus on muscle contractions of increasing forces, the amplitude of the M-wave frst phase decreased (~20%, P<0.05), that of the second phase increased (~30%, P<0.05), and M-wave duration decreased (~30%, P<0.05) as force was raised from 0 to 60–70% MVC force. Conclusions The present results will help to identify the adjustments in the M-wave profle caused by muscle shortening and also contribute to diferentiate these adjustments from those caused by muscle fatigue and/or changes in Na+–K+ pump activity.
Open Access
Understanding EMG PDF changes with motor unit potential amplitudes, firing rates, and noise level through EMG filling curve analysis
(IEEE, 2024-08-30) Navallas Irujo, Javier; Mariscal Aguilar, Cristina; Malanda Trigueros, Armando; Rodríguez Falces, Javier; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza
EMG filling curve characterizes the EMG filling process and EMG probability density function (PDF) shape change for the entire force range of a muscle.We aim to understand the relation between the physiological and recording variables, and the resulting EMG filling curves. We thereby present an analytical and simulation study to explain how the filling curve patterns relate to specific changes in the motor unit potential (MUP) waveforms and motor unit (MU) firing rates, the two main factors affecting the EMG PDF, but also to recording conditions in terms of noise level. We compare the analytical results with simulated cases verifying a perfect agreement with the analytical model. Finally, we present a set of real EMG filling curves with distinct patterns to explain the information about MUP amplitudes, MU firing rates, and noise level that these patterns provide in the light of the analytical study. Our findings reflect that the filling factor increases when firing rate increases or when newly recruited motor unit have potentials of smaller or equal amplitude than the former ones. On the other hand, the filling factor decreases when newly recruited potentials are larger in amplitude than the previous potentials. Filling curves are shown to be consistent under changes of the MUP waveform, and stretched under MUP amplitude scaling. Our findings also show how additive noise affects the filling curve and can even impede to obtain reliable information from the EMG PDF statistics.
Open Access
Motor unit profile: a new way to describe the scanning-EMG potential
(Elsevier, 2017) Corera Orzanco, Íñigo; Malanda Trigueros, Armando; Rodríguez Falces, Javier; Porta Cuéllar, Sonia; Navallas Irujo, Javier; Ingeniería Eléctrica y Electrónica; Ingeniaritza Elektrikoa eta Elektronikoa
The motor unit profile, a representation of the trajectories of positive and negative turns of a scanning-EMG signal, is a new way to characterize the motor unit potential. Such characterization allows quantification of the scanning-EMG signal's complexity, which is closely related to the anatomy and physiology of the motor unit. To extract the motor unit profile, an algorithm that detects the turns of the scanning-EMG signal and links them using point-tracking techniques has been developed. The performance of this algorithm is sensitive to three parameters: the turn detection threshold, the maximum tracking interval threshold, and the trajectory purge threshold. Real scanning-EMG signals have been used to analyze the algorithm's behavior and the influence of the algorithm's parameters and to determine which parameter values provide the best performance.
Open Access
Masked least-squares averaging in processing of scanning-EMG recordings with multiple-discharges
(Springer, 2020) Corera Orzanco, Íñigo; Malanda Trigueros, Armando; Rodríguez Falces, Javier; Navallas Irujo, Javier; Ingeniería Eléctrica y Electrónica; Ingeniaritza Elektrikoa eta Elektronikoa
Removing artifacts from nearby motor units is one of the main objectives when processing scanning-EMG recordings. Methods such as median filtering or masked least-squares smoothing (MLSS) can be used to eliminate artifacts in recordings with just one discharge of the motor unit potential (MUP) at each location. However, more effective artifact removal can be achieved if several discharges per position are recorded. In this case, processing usually involves averaging the discharges available at each position and then applying a median filter in the spatial dimension. The main drawback of this approach is that the median filter tends to distort the signal waveform. In this paper, we present a new algorithm that operates on multiple discharges simultaneously and in the spatial dimension. We refer to this algorithm as the multi masked least-squares smoothing (MMLSS) algorithm: an extension of the MLSS algorithm for the case of multiple discharges. The algorithm is tested using simulated scanning-EMG signals in different recording conditions, i.e., at different levels of muscle contraction and for different numbers of discharges per position. Results demonstrate that the algorithm eliminates artifacts more effectively than any previously available method and does so without distorting the waveform of the signal.
Open Access
EMG probability density function: a new way to look at EMG signal filling from single motor unit potential to full interference pattern
(IEEE, 2023) Navallas Irujo, Javier; Eciolaza Ferrando, Adrián; Mariscal Aguilar, Cristina; Malanda Trigueros, Armando; Rodríguez Falces, Javier; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
An analytical derivation of the EMG signal's amplitude probability density function (EMG PDF) is presented and used to study how an EMG signal builds-up, or fills, as the degree of muscle contraction increases. The EMG PDF is found to change from a semi-degenerate distribution to a Laplacian-like distribution and finally to a Gaussian-like distribution. We present a measure, the EMG filling factor, to quantify the degree to which an EMG signal has been built-up. This factor is calculated from the ratio of two non-central moments of the rectified EMG signal. The curve of the EMG filling factor as a function of the mean rectified amplitude shows a progressive and mostly linear increase during early recruitment, and saturation is observed when the EMG signal distribution becomes approximately Gaussian. Having presented the analytical tools used to derive the EMG PDF, we demonstrate the usefulness of the EMG filling factor and curve in studies with both simulated signals and real signals obtained from the tibialis anterior muscle of 10 subjects. Both simulated and real EMG filling curves start within the 0.2 to 0.35 range and rapidly rise towards 0.5 (Laplacian) before stabilizing at around 0.637 (Gaussian). Filling curves for the real signals consistently followed this pattern (100% repeatability within trials in 100% of the subjects). The theory of EMG signal filling derived in this work provides (a) an analytically consistent derivation of the EMG PDF as a function of motor unit potentials and motor unit firing patterns; (b) an explanation of the change in the EMG PDF according to degree of muscle contraction; and (c) a way (the EMG filling factor) to quantify the degree to which an EMG signal has been built-up.
Open Access
Association of intrinsic capacity with incidence and mortality of cardiovascular disease: prospective study in UK Biobank
(Wiley, 2023) Ramírez Vélez, Robinson; Iriarte-Fernández, María; Santafé Rodrigo, Guzmán; Malanda Trigueros, Armando; Beard, John R.; García Hermoso, Antonio; Izquierdo Redín, Mikel; Ciencias de la Salud; Estadística, Informática y Matemáticas; Ingeniería Eléctrica, Electrónica y de Comunicación; Institute for Advanced Materials and Mathematics - INAMAT2; Osasun Zientziak; Estatistika, Informatika eta Matematika; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
Background: The World Health Organization proposed the concept of intrinsic capacity (IC; the composite of all the physical and mental capacities of the individual) as central for healthy ageing. However, little research has investigated the interaction and joint associations of IC with cardiovascular disease (CVD) incidence and CVD mortality in middle- and older-aged adults. Methods: Using data from 443 130 UK Biobank participants, we analysed seven biomarkers capturing the level of functioning of five domains of IC to calculate a total IC score (ranging from 0 [better IC] to +4 points [poor IC]). Associations between IC score and incidence of six long-term CVD conditions (hypertension, stroke/transient ischaemic attack stroke, peripheral vascular disease, atrial fibrillation/flutter, coronary artery disease and heart failure), and grouped mortality from these conditions were estimated using Cox proportional models, with a 1-year landmark analysis to triangulate the findings. Results: Over 10.6 years of follow-up, CVD morbidity grouped (n = 384 380 participants for the final analytic sample) was associated with IC scores (0 to +4): mean hazard ratio (HR) [95% confidence interval, CI] 1.11 [1.08–1.14], 1.20 [1.16–1.24], 1.29 [1.23–1.36] and 1.56 [1.45–1.59] in men (C-index = 0.68), and 1.17 [1.13–1.20], 1.30 [1.26–1.36], 1.52 [1.45–1.59] and 1.78 [1.67–1.89] in women (C-index = 0.70). In regard to mortality, our results indicated that the higher IC score (+4 points) was associated with a significant increase in subsequent CVD mortality (mean HR [95% CI]: 2.10 [1.81–2.43] in men [C-index = 0.75] and 2.29 [1.85–2.84] in women [C-index = 0.78]). Results of all sensitivity analyses by full sample, sex and age categories were largely consistent independent of major confounding factors (P < 0.001). Conclusions: IC deficit score is a powerful predictor of functional trajectories and vulnerabilities of the individual in relation to CVD incidence and premature death. Monitoring an individual's IC score may provide an early-warning system to initiate preventive efforts.
Open Access
Independent component analysis as a tool to eliminate artifacts in EEG. A quantitative study
(Lippincott, Williams & Wilkins, 2003) Iriarte, Jorge; Urrestarazu, Elena; Valencia Ustárroz, Miguel; Alegre, Manuel; Malanda Trigueros, Armando; Viteri, César; Artieda, Julio; Ingeniería Eléctrica y Electrónica; Ingeniaritza Elektrikoa eta Elektronikoa
Independent component analysis (ICA) is a novel technique that calculates independent components from mixed signals. A hypothetical clinical application is to remove artifacts in EEG. The goal of this study was to apply ICA to standard EEG recordings to eliminate well-known artifacts, thus quantifying its efficacy in an objective way. Eighty samples of recordings with spikes and evident artifacts of electrocardiogram (EKG), eye movements, 50-Hz interference, muscle, or electrode artifact were studied. ICA components were calculated using the Joint Approximate Diagonalization of Eigen-matrices (JADE) algorithm. The signal was reconstructed excluding those components related to the artifacts. A normalized correlation coefficient was used as a measure of the changes caused by the suppression of these components. ICA produced an evident clearing-up of signals in all the samples. The morphology and the topography of the spike were very similar before and after the removal of the artifacts. The correlation coefficient showed that the rest of the signal did not change significantly. Two examiners independently looked at the samples to identify the changes in the morphology and location of the discharge and the artifacts. In conclusion, ICA proved to be a useful tool to clean artifacts in short EEG samples, without having the disadvantages associated with the digital filters. The distortion of the interictal activity measured by correlation analysis was minimal.
Open Access
Modelling fibrillation potentials: analysis of time parameters in the muscle intracellular action potential
(IEEE, 2007) Rodríguez Falces, Javier; Malanda Trigueros, Armando; Gila Useros, Luis; Rodríguez Carreño, Ignacio; Navallas Irujo, Javier; Ingeniería Eléctrica y Electrónica; Ingeniaritza Elektrikoa eta Elektronikoa
A single fibre action potential (SFAP) can be modelled as the convolution of a biolectrical source and a filter impulse response. In the Dimitrov-Dimitrova (D-D) convolutional model, the first temporal derivative of the intracellular action potential (IAP) is used as the source, and T spl is a time parameter related to the duration of the IAP waveform. Our work is centred on the relation between Tspl and the main spike duration (MSD), defined as the time interval between the first and third phases of the SFAP. We show that Tspl essentially determines the MSD parameter. As experimental data, we used fibrillation potentials (FPs) of two different muscles to study the D-D model. We found that T spl should have a certain statistical variability in order to explain the variability in the MSD of our FPs. In addition, we present a method to estimate the T spl values corresponding to a given SFAP from its measured MSD.
Open Access
A masked least-squares smoothing procedure for artifact reduction in scanning-EMG recordings
(Springer, 2018) Corera Orzanco, Íñigo; Eciolaza Ferrando, Adrián; Rubio Zamora, Oliver; Malanda Trigueros, Armando; Rodríguez Falces, Javier; Navallas Irujo, Javier; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
Scanning-EMG is an electrophysiological technique in which the electrical activity of the motor unit is recorded at multiple points along a corridor crossing the motor unit territory. Correct analysis of the scanning-EMG signal requires prior elimination of interference from nearby motor units. Although the traditional processing based on the median filtering is effective in removing such interference, it distorts the physiological waveform of the scanning-EMG signal. In this study, we describe a new scanning-EMG signal processing algorithm that preserves the physiological signal waveform while effectively removing interference from other motor units. To obtain a cleaned-up version of the scanning signal, the masked least-squares smoothing (MLSS) algorithm recalculates and replaces each sample value of the signal using a least-squares smoothing in the spatial dimension, taking into account the information of only those samples that are not contaminated with activity of other motor units. The performance of the new algorithm with simulated scanning-EMG signals is studied and compared with the performance of the median algorithm and tested with real scanning signals. Results show that the MLSS algorithm distorts the waveform of the scanning-EMG signal much less than the median algorithm (approximately 3.5 dB gain), being at the same time very effective at removing interference components.