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Publications (12)
Several methods have been developed in biomedical signal processing to extract the envelope and features of electromyography (EMG) signals and predict human motion. Also, efforts were made to use this information to improve the interaction of a human body and artificial protheses. The main operations here are envelope acquiring, artifacts filtering...
Environmental monitoring requires an analysis of large and reliable amount of data collected through node stations distributed over a very wide area. Equipment used in such stations are often expensive that limits the amount of sensing stations to be deployed. The technology known as Wireless Sensor Networks (WNS) is a viable option to deliver low-...
Accuracy and stability of the myoelectric prosthetic arm digital proportional control strongly depends on shape of the rectified motor unit action potential (MUAP) envelope. To mitigate effects caused by the envelope-induced torque ripples, mechanical vibrations (TRMV), and electromechanical delays (EMD), in this paper we develop in discrete-time s...
Environmental monitoring requires an analysis of large and reliable amount of data collected through node stations distributed over a very wide area. Equipments used in such stations are often expensive that limits the amount of sensing stations to be deployed. The technology known as Wireless Sensor Networks (WNS) is a viable option to deliver low...
In this paper, we proposed a system to integrate optical and electronic instrumentation devices to predict a mode-locking fiber laser response, using a remote data acquisition with processing through an artificial neural network (ANN). The system is made up of an optical spectrum analyzer (OSA), oscilloscope (OSC), polarimeter (PAX), and the data a...
This paper develops the Kalman filter (KF) and unbiased finite impulse response (UFIR) filter to extract the electromyography (EMG) signal envelope and remove some artifacts with a maximum accuracy assuming colored measurement noise (CMN). The filters are developed in discrete-time state-space for Gauss-Markov CMN and termed as cKF and cUFIR. For E...
This article describes some filtering methods to remove artifacts from the EMG signal envelope. Diverse EMG waveforms are studied using the Kalman filter (KF) and unbiased finite impulse response (UFIR) filter. The filters are developed in discrete-time state-space for Gauss-Markov colored measurement noise (CMN) and termed as cKF and cUFIR. It is...
