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 - 3 of 3
  • 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.
  • 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.