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In this study, programmable current source (PCS) experimental set-up that measures the nerve conduction velocity is designed. Firstly, analog PCS is implemented with integrated circuit of 555. Then, microprocessor-based PCS is designed by improving existing analog design at hand. PCS can produce current signal with adjustable frequency and amplitude. An EMG amplifier circuit is designed to measure...
In this study, two channels, multifunctional myoelectric prosthesis hand is designed and operated for biomedical and control engineering departments laboratory as experiment apparatus. Various analog signal processing steps are implemented to the surface EMG signals which received on the triceps and biceps muscles. After that signals are conveyed to microcontroller and compared with a threshold value...
This paper investigate a fuzzy logic based high performance surface EMG classification algorithm for multifunctional upper limb prostheses. In this paper, we record 4 channels EMG data with surface electrodes from the forearm and aimed to recognize 8 different upper limb movements using heuristic fuzzy logic methods from these data. We use 50 surface EMG data for every function and evaluate the performance...
This study includes a classification structure consisting of second part for the automatic diagnosis of the neuromuscular disease of ALS (Amyotrophic Lateral Sclerosis) and myopathy being a muscular disease. In this study feature vectors containing time domain parameters, frequency domain parameters (a total of 25 feature vectors) as well as feature vectors composed of combination of these parameters...
In this study, Virtual Prosthetic Hand that controlled by single and dual channel sEMG (surface EMG) signals is presented. Virtual hand is designed by Blender 3D that is a powerful graphic modelling tool. Additionally, processing of raw EMG signal is explained with MATLAB. Python software language which has a large library was used for importing and evaluating of signals and for control algorithms...
This study includes a classification structure consisting of first three stages for the automatic diagnosis of the neuromuscular disease of ALS (Amyotrophic Lateral Sclerosis) and myopathy being a muscular disease. In this study; EMG mark representing best MUAP will be determined for the right to comment sign EMG. After the first stage of the raw EMG data eliminated by noise the segmentation stage...
In this paper, an estimation of angle of hand opening-closing movements by using the Artificial Neural Network (ANN) from surface electromyography (sEMG) signal is presented. The first step of this method is to record sEMG signal from the subject's right forearm and to acquired video frames of hand at the same time. The second step is to synchronize the beginning and the end of recorded video frame...
In this study, SVM (Support Vector Machine) algorithm is used for the diagnosis of ALS which is the most common type of motor neuron disease. Before classification of EMG data with SVM (Support Vector Machine); pre-processing, segmentation, feature extraction and clustering stages of data are completed. In the stage of clustering, hybrid and hierarchical clustering methods are employed. After that,...
In this study, we have investigated usefulness of extraction of the surface electromiyogram (sEMG) features from multi-level wavelet decomposition of the yEMG signal. The first step of this method is to analyze sEMG signal detected from the subject's right upper forearm and extract features using the mean absolute value (MAV), MAV of wavelet approximation and details coefficients, MAV of wavelet approximation...
In this paper, an prediction speed method of hand open-çlose by using the Artificial Neural Network (ANN) surface electromyography (sEMG) signal is presented. The first step of this method is to analyze sEMG signal detected from the subject's right upper forearm and extract features using the mean absolute value (MAV), the root mean square (RMS), the variance (VAR), the standart deviation (STD), the...
Electromyography (EMG) is a medical measurement system. EMG measurements are required for the diagnosis of some diseases and used in order to facilitate physicians' work. In this study, MUAPs' in an EMG data set that contains both healthy and Amyotrophic Lateral Sclerosis (ALS) disease subjects are represented in time domain and frequency domain with a total of 10 feature vectors. Two pattern recognition...
This paper presents a systematic construction of linearly weighted Gaussian radial basis function (RBF) neural network. The proposed method is computationally a two-stage hybrid training algorithm. The first stage of the hybrid algorithm is a pre-processing unit which generates a coarsely-tuned RBF network. The second stage is a fine-tuning phase. The coarsely-tuned RBF network is then optimized by...
This paper reviews some frequently used methods to initialize an radial basis function (RBF) network and presents systematic design procedures for pre-processing unit(s) to initialize RBF network from available input–output data sets. The pre-processing units are computationally hybrid two-step training algorithms that can be named as (1) construction of initial structure and (2) coarse-tuning of...
Development of technology increased the attention of the research community on power quality (PQ) disturbance classification problem. This paper presents wavelet based effective feature extraction method and support vector machines (SVM) for PQ disturbance classification problem. Two common kinds of power quality disturbances, voltage sag and swell, are considered in this paper. After multi-resolution...
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