Person:
Malanda Trigueros, Armando

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Malanda Trigueros

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Armando

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Ingeniería Eléctrica, Electrónica y de Comunicación

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ISC. Institute of Smart Cities

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0000-0002-3122-9049

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379

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Now showing 1 - 6 of 6
  • PublicationOpen 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.
  • PublicationOpen 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.
  • PublicationOpen 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.
  • PublicationOpen 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.
  • PublicationOpen Access
    Métodos de procesamiento y análisis de señales electromiográficas
    (Gobierno de Navarra, 2009) Gila Useros, Luis; Malanda Trigueros, Armando; Rodríguez Carreño, Ignacio; Rodríguez Falces, Javier; Navallas Irujo, Javier; Ingeniería Eléctrica y Electrónica; Ingeniaritza Elektrikoa eta Elektronikoa
    La electromiografía clínica es una metodología de registro y análisis de la actividad bioeléctrica del músculo esquelético orientada al diagnóstico de las enfermedades neuromusculares. Las posibilidades de aplicación y el rendimiento diagnóstico de la electromiografía han evolucionado paralelamente al conocimiento de las propiedades de la energía eléctrica y al desarrollo de la tecnología eléctrica y electrónica. A mediados del siglo XX se introdujo el primer equipo comercial de electromiografía para uso médico basado en circuitos electrónicos analógicos. El desarrollo posterior de la tecnología digital ha permitido disponer de sistemas controlados por microprocesadores cada vez más fiables y potentes para captar, representar, almacenar, analizar y clasificar las señales mioeléctricas. Es esperable que el avance de las nuevas tecnologías de la información y la comunicación pueda conducir en un futuro próximo a la aplicación de desarrollos de inteligencia artificial que faciliten la clasificación automática de señales así como sistemas expertos de apoyo al diagnóstico electromiográfico.
  • PublicationOpen Access
    Motor unit action potential duration, I: variability of manual and automatic measurements
    (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 analyze the variability in manual measurements of motor unit action potential (MUAP) duration and to evaluate the effectiveness of well-known algorithms for automatic measurement. Two electromyographists carried out three independent duration measurements of a set of 240 MUAPs. The intraexaminer and interexaminer variabilities were analyzed by means of the Gage Reproducibility and Repeatability method. The mean of the three closest manually marked positions was considered the gold standard of the duration markers positions (GSP). The results of four wellknown automatic methods for estimating MUAP duration were compared with the GSP. Manual measurements of duration showed a lot of variability, with the combined intraoperator and interoperator variability greater than 30%. The greatest difference between manual positions was 11.2 ms. The mean differences between the GSP and those obtained with the four automatic methods ranged between 0.6 and 8.5 ms. Both manual and automatic measurements of MUAP duration show a high degree of variability. More precise methods are needed to improve the accuracy and reliability of the estimates of this parameter.