Open Access
A new muscle architecture model with non-uniform distribution of muscle fiber types
(World Academy of Science, Engineering and Technology, 2007) Navallas Irujo, Javier; Malanda Trigueros, Armando; Gila Useros, Luis; Rodríguez Falces, Javier; Rodríguez Carreño, Ignacio; Ingeniería Eléctrica y Electrónica; Ingeniaritza Elektrikoa eta Elektronikoa
According to previous studies, some muscles present a non-homogeneous spatial distribution of its muscle fiber types and motor unit types. However, available muscle models only deal with muscles with homogeneous distributions. In this paper, a new architecture muscle model is proposed to permit the construction of non-uniform distributions of muscle fibers within the muscle cross section. The idea behind is the use of a motor unit placement algorithm that controls the spatial overlapping of the motor unit territories of each motor unit type. Results show the capabilities of the new algorithm to reproduce arbitrary muscle fiber type distributions.
Open Access
Análisis del proceso de llenado de la señal sEMG a medida que aumenta gradualmente la fuerza en el cuádriceps
(Sociedad Española de Ingeniería Biomédica, 2024) Recalde Villamayor, Silvia; Navallas Irujo, Javier; Mariscal Aguilar, Cristina; Rodríguez Falces, Javier; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza; Institute of Smart Cities - ISC
Objetivos: No existe una comprensión completa del modo en que la señal EMG de superficie se llena progresivamente de potenciales de unidad motora (MUP) a medida que aumenta la fuerza. Intentamos investigar este proceso de llenado de sEMG. Métodos: Se registraron señales EMG superficiales del cuádriceps de sujetos sanos a medida que la fuerza aumentaba gradualmente de 0 a 40% MVC. El proceso de llenado sEMG se analizó midiendo el factor de llenado EMG (calculado a partir de los momentos no centrales de la señal sEMG rectificada). Resultados: (1) Al aumentar gradualmente la fuerza, aparecieron uno o dos saltos bruscos prominentes en la amplitud del sEMG entre el 0 y el 10% de la fuerza MVC en los vastos lateral y medial. (2) Los saltos de amplitud se originaban cuando aparecían en la señal de sEMG unos pocos MUP de gran amplitud, que destacaban claramente de la actividad de sEMG anterior. (3) Cada vez que se producía un salto brusco en la amplitud del sEMG, se iniciaba una nueva fase de llenado del sEMG. Conclusiones: El proceso de llenado del sEMG tuvo una o dos etapas en los músculos vastos, estando el sEMG casi completamente lleno a fuerzas muy bajas (2-12% MVC). Importancia: El factor de llenado es una herramienta prometedora útil para analizar el proceso de llenado EMG.
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
Motor unit action potential duration, II: a new automatic measurement method based on the wavelet transform
(Lippincott, Williams & Wilkins, 2007) Rodríguez Carreño, Ignacio; Gila Useros, Luis; Malanda Trigueros, Armando; García Gurtubay, Ignacio; Mallor Giménez, Fermín; Gómez Elvira, Sagrario; Rodríguez Falces, Javier; Navallas Irujo, Javier; Ingeniería Eléctrica y Electrónica; Estadística e Investigación Operativa; Ingeniaritza Elektrikoa eta Elektronikoa; Estatistika eta Ikerketa Operatiboa
To present and evaluate a new algorithm, based on the wavelet transform, for the automatic measurement of motor unit action potential (MUAP) duration. A total of 240 MUAPs were studied. The waveform of each MUAP was wavelet-transformed, and the start and end points were estimated by regarding the maxima and minima points in a particular scale of the wavelet transform. The results of the new method were compared with the gold standard of duration marker positions obtained by manual measurement. The new method was also compared with a conventional algorithm, which we had found to be best in a previous comparative study. To evaluate the new method against manual measurements, the dispersion of automatic and manual duration markers were analyzed in a set of 19 repeatedly recorded MUAPs. The differences between the new algorithm’s marker positions and the gold standard of duration marker positions were smaller than those observed with the conventional method. The dispersion of the new algorithm’s marker positions was slightly less than that of the manual one. Our new method for automatic measurement of MUAP duration is more accurate than other available algorithms and more consistent than manual measurements.
Open Access
Actividad electromiográfica (EMG) durante el pedaleo, su utilidad en el diagnóstico de la fatiga en ciclistas
(SEMED - FEMEDE, 2017) Córdova Martínez, Alfredo; Nuin, Iván; Fernández-Lázaro, Diego; Latasa Zudaire, Iban Alexander; Rodríguez Falces, Javier; Ingeniería Eléctrica y Electrónica; Ingeniaritza Elektrikoa eta Elektronikoa
La fatiga muscular tiene múltiples definiciones, pero con una misión especial cual es la misión protectora, avisando al organismo sobre la debilidad o la aparición de una incapacidad funcional. En esta revisión se hace un análisis de las aplicaciones de la electromiografía (EMG) como técnica para comprender los patrones de activación musculares durante el pedaleo y la aparición de fatiga muscular. Se ha realizado una revisión en la cual se analizan las variaciones de la actividad EMG durante las fases del pedaleo. El movimiento del pedaleo ha sido estudiado exhaustivamente y se ha legado a distinguir 4 fases en el pedaleo que originan la propulsión y el recobro. Mediante el uso de la EMG se pueden describir los patrones de activación típicos, en cuanto al nivel de actividad y el tiempo de activación de los principales músculos de las extremidades inferiores. La actividad muscular y la coordinación pueden variar entre personas a lo largo de un solo ciclo de pedaleo y entre diferentes ciclos de la misma persona. También se examinan los principales factores que pueden influir en estos patrones EMG durante las fases del pedaleo. Asimismo, se describe la influencia de factores como la potencia de salida, cadencia o frecuencia de pedaleo, pendiente y postura, interfaz calzado pedal, nivel de entrenamiento y fatiga muscular, que producen alteraciones en el tiempo de activación y coordinación muscular.
Open Access
The first and second phases of the muscle compound action potential in the thumb are differently affected by electrical stimulation trains
(American Physiological Society, 2024) Lanfranchi, Clément; Rodríguez Falces, Javier; Place, Nicolas; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza; Institute of Smart Cities - ISC
Sarcolemmal membrane excitability is often evaluated by considering the peak-to-peak amplitude of the compound muscle action potential (M wave). However, the first and second M-wave phases represent distinct properties of the muscle action potential, which are differentially affected by sarcolemma properties and other factors such as muscle architecture. Contrasting with previous studies in which voluntary contractions have been used to induce muscle fatigue, we used repeated electrically induced tetanic contractions of the adductor pollicis muscle and assessed the kinetics of M-wave properties during the course of the contractions. Eighteen participants (24 ± 6 yr; means ± SD) underwent 30 electrically evoked tetanic contractions delivered at 30 Hz, each lasting 3 s with 1 s intervals. We recorded the amplitudes of the first and second M-wave phases for each stimulation. During the initial stimulation train, the first and second M-wave phases exhibited distinct kinetics. The first phase amplitude showed a rapid decrease to reach ~59% of its initial value (P < 0.001), whereas the second phase amplitude displayed an initial transient increase of ~19% (P ¼ 0.007). Within subsequent trains, both the first and second phase amplitudes consistently decreased as fatigue developed with a reduction during the last train reaching ~47% of its initial value (P < 0.001). Analyzing the first M wave of each stimulation train unveiled different kinetics for the first and second phases during the initial trains, but these distinctions disappeared as fatigue progressed. These findings underscore the interplay of factors affecting the M wave and emphasize the significance of separately scrutinizing its first and second phases when assessing membrane excitability adjustments during muscle contractions.
Open Access
Correlation between discharge timings of pairs of motor units reveals the presence but not the proportion of common synaptic input to motor neurons
(American Physiological Society, 2017) Rodríguez Falces, Javier; Negro, Francesco; Farina, Dario; Ingeniería Eléctrica y Electrónica; Ingeniaritza Elektrikoa eta Elektronikoa
We investigated whether correlation measures derived from pairs of motor unit (MU) spike trains are reliable indicators of the degree of common synaptic input to motor neurons. Several 50-s isometric contractions of the biceps brachii muscle were performed at different target forces ranging from 10 to 30% of the maximal voluntary contraction relying on force feedback. Forty-eight pairs of MUs were examined at various force levels. Motor unit synchrony was assessed by cross-correlation analysis using three indexes: the output correlation as the peak of the cross-histogram (ρ) and the number of synchronous spikes per second (CIS) and per trigger (E). Individual analysis of MU pairs revealed that ρ, CIS, and E were most often positively associated with discharge rate (87, 85, and 76% of the MU pairs, respectively) and negatively with interspike interval variability (69, 65, and 62% of the MU pairs, respectively). Moreover, the behavior of synchronization indexes with discharge rate (and interspike interval variability) varied greatly among the MU pairs. These results were consistent with theoretical predictions, which showed that the output correlation between pairs of spike trains depends on the statistics of the input current and motor neuron intrinsic properties that differ for different motor neuron pairs. In conclusion, the synchronization between MU firing trains is necessarily caused by the (functional) common input to motor neurons, but it is not possible to infer the degree of shared common input to a pair of motor neurons on the basis of correlation measures of their output spike trains.
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
Evaluation of the electromyography test for the analysis of the aerobic-anaerobic transition in elite cyclists during incremental exercise
(MDPI, 2019) Latasa Zudaire, Iban Alexander; Córdova Martínez, Alfredo; Quintana Ortí, Gregorio; Lavilla Oiz, Ana; Navallas Irujo, Javier; Rodríguez Falces, Javier; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
(1) Background: The aim of this study was to investigate the validity and reliability of surface electromyography (EMG) for automatic detection of the aerobic and anaerobic thresholds during an incremental continuous cycling test using 1 min exercise periods in elite cyclists. (2) Methods: Sixteen well-trained cyclists completed an incremental exercise test (25 W/1 min) to exhaustion. Surface bipolar EMG signals were recorded from the vastus lateralis, vastus medialis, biceps femoris, and gluteus maximus, and the root mean square (RMS) were assessed. The multi-segment linear regression method was used to calculate the first and second EMG thresholds (EMG(T1) and EMG(T2)). During the test, gas exchange data were collected to determine the first and second ventilatory thresholds (VT1 and VT2). (3) Results: Two breakpoints (thresholds) were identified in the RMS EMG vs. time curve for all muscles in 75% of participants. The two breakpoints, EMG(T1) and EMG(T2) , were detected at around 70%-80% and 90%-95% of VO2MAX, respectively. No significant differences were found between the means of VT(1 )and EMGT(1) for the vastii and biceps femoris muscles (p > 0.05). There were no significant differences between means of EMG(T2) and VT2 (p > 0.05). (4) Conclusions: It is concluded that the multi-segment linear regression algorithm is a valid non-invasive method for analyzing the aerobic-anaerobic transition during incremental tests with 1 min stage durations.
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.

Rodríguez Falces, Javier

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