ABSTRACT
The objective of this work was the study and the development of techniques for acquiring and processing electromyographic signals that can be used for analysis of the behavior of electromyographic variables during fatiguing dynamic activities. Two of the techniques were the RMS value and the MPF, which are commonly used for the analysis of electromyographic signals measured during isometric contractions. A new technique, called MAEC, was proposed, based on the domain of the Wavelet transform. The results showed that the combination of the three techniques together with the protocol for recording electromyographic signals lead to a useful characterization of the behavior of electromygraphic variables.
Subject(s)
Action Potentials/physiology , Algorithms , Electromyography/methods , Muscle Contraction/physiology , Muscle Fatigue/physiology , Muscle, Skeletal/physiology , Signal Processing, Computer-Assisted , Adult , Female , Humans , Male , Reproducibility of Results , Sensitivity and SpecificityABSTRACT
This article presents an algorithm for compression of echocardiographic images. The algorithm is based on the JPEG algorithm and uses a fuzzy inference system to adapt the normalization process of the transformed coefficients through the analysis of the local characteristics of echocardiographic images. The images considered in this paper were acquired in actual echocardiography exams. The proposed encoder guarantees a maximum local signal-to-noise ratio, which is adapted to the characteristics of each sub-block of the image.
