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In this study the EMG data that are collected from 25 subjects were analyzed. Two separate groups of myopathy and ALS patients and a control group are the participants of the research. Both females and males are included in the all groups. We preprocessed the EMG signals and used autoregressive method (AR) and discrete wavelet method (DWT) for feature extraction. Features are applied to various classification algorithms, namely Multilayer perceptron, C 4,5, CART, K-NN, Random forest tree.

Produktbeschreibung
In this study the EMG data that are collected from 25 subjects were analyzed. Two separate groups of myopathy and ALS patients and a control group are the participants of the research. Both females and males are included in the all groups. We preprocessed the EMG signals and used autoregressive method (AR) and discrete wavelet method (DWT) for feature extraction. Features are applied to various classification algorithms, namely Multilayer perceptron, C 4,5, CART, K-NN, Random forest tree.
Autorenporträt
Emine Yaman received the BS,MS and PhD degree in Medical Informatics and Computer Science from Vienna University of Technology, Austria.Her areas of interests are data mining, biomedical signal processing, artificial intelligence, machine learning. She is voluntarily serving as a technical publication reviewer for many respected scientific journals