RESUMEN
Self-assembled InN nanocolumns were grown at low temperatures by plasma-assisted molecular beam epitaxy with a high crystalline quality. The self-assembling procedure was carried out on AlN/Al layers on Si(111) substrates avoiding the masking process. The Al interlayer on the Si(111) substrate prevented the formation of amorphous SiN. We found that the growth mechanism at 400 ∘ C of InN nanocolumns started by a layer-layer (2D) nucleation, followed by the growth of 3D islands. This growth mechanism promoted the nanocolumn formation without strain. The nanocolumnar growth proceeded with cylindrical and conical shapes with heights between 250 and 380 nm. Detailed high-resolution transmission electron microscopy analysis showed that the InN nanocolumns have a hexagonal crystalline structure, free of dislocation and other defects. The analysis of the phonon modes also allowed us to identify the hexagonal structure of the nanocolumns. In addition, the photoluminescence spectrum showed an energy transition of 0.72 eV at 20 K for the InN nanocolumns, confirmed by photoreflectance spectroscopy.
RESUMEN
Resumen Este trabajo presenta el desarrollo de un sistema de adquisición y procesamiento de señales mioeléctricas superficiales o SEMG. El sistema propuesto adquiere las señales SEMG de la superficie de la piel utilizando electrodos superficiales de AgCl. El sistema tiene una etapa de amplificación y de filtrado por hardware para eficientar el tiempo de proceso. Se desarrolló un software para procesar por transformada de Fourier la señal SEMG amplificada y filtrada. A diferencia de otros sistemas de adquisición de señales biológicas que son desarrollados para terapia o rehabilitación, este sistema está pensado para ser usado para el control de brazos robóticos, por ello el software desarrollado mide la fatiga utilizando parámetros como el corrimiento de la frecuencia media instantánea y la densidad espectral de potencia de la señal SEMG.
Abstract This paper presents the development of a system for acquiring and processing of surface myoelectric signals or SEMG. The proposed system acquires signals SEMG skin surface using AgCl surface electrodes. The system has an amplification step and hardware filtering to streamline the processing time. Developed software for processing the Fourier transform SEMG amplified and filtered signal. Unlike other systems for acquisition of biological signals, which are developed for therapy or rehabilitation, this system is intended to be used for the control of robotic arms, so the software performs the measurement of fatigue using parameters like bleed average frequency and instantaneous power spectral density of the signal SEMG.