Toufik Bakir

Estimation of Muscular Fatigue Under Electromyostimulation Using CWT

The aim of this study is to investigate muscular fatigue and to propose a new fatigue index based on the continuous wavelet transform (CWT) which is compared to the standard fatigue indexes from literature. Fatigue indexes are all based on the electrical activity of muscles [electromyogram (EMG)] acquired during an electrically stimulated contraction thanks to two modules (electromyostimulation + electromyography recording) that can analyze EMG signals in real time during electromyostimulation. The extracted parameters are compared with each other and their sensitivity to noise is studied. The effect of truncation of M waves is then investigated, enlightening the robustness of the index obtained using CWT.

A mixed FES/EMG system for real time analysis of muscular fatigue

In this article, we present a functional electrical stimulator allowing the extraction in real time of M-wave characteristics from resulting EMG recodings in order to quantify muscle fatigue. This system is composed of three parts. A Labview software managing the stimulation output and electromyogram (EMG) input signal, a hardware part amplifying the output and input signal and a link between the two previous parts which is made up from input/output module (NIdaq USB 6251). In order to characterize the fatigue level, the Continuous Wavelet Transform is applied yielding a local maxima detection. The fatigue is represented on a scale from 0 for a fine shaped muscle to 100 for a very tired muscle. Premilary results are given.

Continuous-discrete observer for crystal size distribution of batch crystallization process

A continuous-discrete observer was designed to estimate the CSD (Crystal Size Distribution) in batch crystallization processes. The observer is based on the discretization of PBE (population balance equations), it describes the evolution of the CSD with the finite difference method. Since the discretization leads a high order model, a reduced model was then constructed in order to simplify the observer synthesis and to reduce the computation time. The observer’s output allows to calculate the moments of the CSD, which may be used for control purposes or process supervision.

Controlling muscular force by functional electrical stimulation using intelligent PID

Functional Electrical Stimulation (FES) appears as a way of extremely promising research today to solve numerous pathology connected to the deficiencies of the nervous system. It is usually used for the rehabilitation of people with neurological disorders. Generally, skeletal muscles are activated by using Constant Frequency Trains (CFTs) with a fixed amplitude and inter-pulse duration. In addition, the systems of electrical stimulation do not adapt the parameters stimulation to obtain a desired force response during the rehabilitation session. The purpose of this study is to adapt automatically the stimulation parameters to the force desired by the clinician with an intelligent PID controller which optimizes the amplitude of pulse in the stimulation pattern.

A Novel Strategy for Adjusting Current Pulse Amplitude of FES-Systems with PID based on PSO Algorithm Method to Control the Muscle Force.

Adjusting stimulation parameters using control strategy based on mathematical model, that successfully predict muscle force, may improve the efficiency of Functional Electrical Stimulation (FES) systems. It present an interesting task in industrial FES systems applications. In the present study, we investigate the PID control tuning based on the Particle Swarm Optimization (PSO) algorithm at the first time in neuro-muscular systems for updating automatically the stimulation pulse amplitude to track a desired force profiles. In the beginning, The PSO algorithm is used to identify unknown force model parameters. Next, according to the identified model, optimal PID gains are found by the same intelligent algorithm. The preliminary obtained results showed promise of using intelligent algorithm on tuning PID to perform control sessions of FES systems.

Model Free Control for muscular force by Functional Electrical Stimulation using pulse width modulation

Functional Electrical Stimulation (FES) is a useful technique for restoring functions for patients with neurological disorders. Muscle activities can be artificially driven through delivery of electrical pulses to skeletal muscles. Typically, muscles are activated by using constant stimulation train with a fixed parameters (amplitude, frequency and pulse width). In addition, the FES systems do not adapt the parameters stimulation to obtain a desired force response during the rehabilitation session. The purpose of this study is to investigate a real-time FES system for adapting automatically the stimulation parameters (stimulation pulse width) to track a desired force. The Model Free Control (MFC) strategy is adopted to compute the pulse width in the stimulation pattern. This strategy is tested with many muscular force references to show their promising control performances.

Estimation of the mean crystal size and the moments of the crystal size distribution in batch crystallization processes

A cascade high gain observer is designed to estimate the first four leading moments of the crystal size distribution (CSD) and the mean crystal size in batch crystallization processes. The proposed observer is based on a well-known transformation of the partial differential equation describing the CSD to a set of ordinary differential equations (the method of moments). Due to numerical difficulties resulting from the important differences in the magnitudes of the moments, a set of new variables is computed to allow a good estimation of the moments and thus the mean crystal size. In this work, only solute concentration and crystallizer temperature are used to estimate the different moments. The performance of the proposed observer is illustrated by simulation using a noisy measurement.

On the control of a muscular force model including muscular fatigue

Electromyostimulation has been used for several decades by athletes or physiotherapists in order to create a muscular reinforcement. However, the efficiency of electromyostimulation is limited by muscular fatigue and by induced pain. Currently, the systems of electromyostimulation do not adapt the stimulation parameters automatically by taking into account physiological parameters such as muscular fatigue. To adapt the stimulation parameters to muscular responses and in order to optimize the rehabilitation sessions, a control of force using an indicator of muscular fatigue could be used. In this paper, we propose two ways to control the force by using a physiological model which includes the effects of muscular fatigue.

Real-time weighting optimization in Chinese Postman Problem

In this study, based on real-time constraint, an optimization method is proposed for solving the problem of the optimal tour. For that, we will construct a graph containing the real-time state of traffic. The collected data will be used to predict the future state traffic and to give an optimized cost of the tour. This optimization is tested in different sizes of the road networks. The results show that the proposed method is efficient and effective in solving the Chinese Postman Problem in real-time.

Truncation effects on muscular fatigue indexes based on M waves analysis

In this paper, we investigate muscular fatigue. We propose a new fatigue index based on the continuous wavelet transform (CWT) and compare it with the standard fatigue indexes from literature. Fatigue indexes are all based on the electrical activity of muscles (electromyogram) acquired during an electrically stimulated contraction (ES). The stimulator and electromyogram system, which were presented in a previous work, allows real-time analysis. The extracted fatigue parameters are compared between each other and their sensitivity to noise is studied. The effect of truncation of M waves is then investigated, enlightening the robustness of the index obtained using CWT.