Sampling frequency and pass-band frequency effects on neuromuscular signals (EMG) recognition

Authors:
Abdelhafid Zeghbib;Frank Palis;Nicola Shoylev;Valeri Mladenov;Nikos Mastorakis
Affiliations:
Otto-von-Guericke-Universität Magdeburg, Institut für Elektrische Energiesysteme, Magdeburg, Germany;Otto-von-Guericke-Universität Magdeburg, Institut für Elektrische Energiesysteme, Magdeburg, Germany;Department of Electrical Engineering, University of Chemical Technology and Metallurgy, Sofia, Bulgaria;Department of Theoretical Electrical Engineering, Technical University of Sofia, Sofia, Bulgaria;Military Institutions of University Education, Hellenic Naval Academy, Piraeus, Greece
Venue:
ISPRA'07 Proceedings of the 6th WSEAS International Conference on Signal Processing, Robotics and Automation
Year:
2007

Citing 1
Cited 2

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Introduction to Digital Signal Processing and Filter Design

Use of RBF neural network in EMG signal noise removal

WSEAS Transactions on Circuits and Systems
Design of adaptive filter using Jordan/Elman neural network in a typical EMG signal noise removal

Advances in Artificial Neural Systems

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Abstract

This paper proposes a new approach for the detection of face regions where the facial features such as eyes, nose, and mouth may exist with very high probability. It uses the characteristic of DCT (discree cosine transformation) that concentrates the ...