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.
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
Técnicas avanzadas de scanning- EMG
(2016) Eciolaza Ferrando, Adrián; Navallas Irujo, Javier; Escuela Técnica Superior de Ingenieros Industriales y de Telecomunicación; Telekomunikazio eta Industria Ingeniarien Goi Mailako Eskola Teknikoa
Este proyecto trata de conseguir la simulación realista de señales electromiográficas (EMG). Para ello, se llevará a cabo la realización e implementación de funciones que permitan simular técnicas de scanning EMG utilizadas en la realidad como el scanning simple, el scanning con N promediados, o técnicas no implementadas como el multiscanning. Con estas funciones se realizarán diversos experimentos con el fin de calcular la influencia de distintos parametros (nivel de contracción voluntario, longitud de la ventana de multiscanning, distancia de las unidades motoras al corredor del electrodo de scanning...) en la obtención de registros EMG. Además, se realizará un estudio de la obtención de registros de multiscanning a partir del cálculo de los trenes de disparo respecto a la descomposición de una señal EMG registrada en un electrodo de trigger
Open Access
Multiscanning-EMG con una aguja
(2018) Eciolaza Ferrando, Adrián; Navallas Irujo, Javier; Escuela Técnica Superior de Ingenieros Industriales y de Telecomunicación; Telekomunikazio eta Industria Ingeniarien Goi Mailako Eskola Teknikoa
Este proyecto trata del estudio de la viabilidad de una nueva técnica para realizar procedimientos de scanning-EMG, denominada multiscanning-EMG con una sola aguja. Al igual que en la técnica de multiscanning-EMG tradicion al, mediante un solo registro será posible obtener múltiples señales de scanning-MUP de unidades motoras cuyos territorios están repartidos a través del corredor de scanning a diferentes profundidades del músculo. Cada scanning-MUP representará la activida d eléctrica espacial y temporal de una unidad motora, al igual que en el scanning-EMG tradicional. Además, esta técnica permitirá registros de multiscanning-EMG utilizando una sola aguja, prescindiendo del uso de agujas de trigger adicionales. En este proyecto se presentan los algoritmos necesarios para la obtención de los scanning-MUPs a partir de la señal EMG en bruto y el diseño de un sistema de evaluación que permitirá analizar el rendimiento de la técnica bajo diferentes condiciones, estableciendo sus ventajas y sus limitaciones.

Eciolaza Ferrando, Adrián

Email Address

person.page.identifierURI

Birth Date

Job Title

Last Name

First Name

person.page.departamento

person.page.instituteName

ORCID

person.page.observainves

person.page.upna

Name

Filters

Author

Subject

Date

Has files

Item Type

Type

Settings

Sort By

Results per page

Search Results