… such as accurate identification of motion and exact modeling of EMG signals, is required to
… This paper presents an EMG pattern recognition method for more accurate identification of a …

… in EMG pattern recognition methods that can be applied to big data analytics. These modern
EMG signal analysis methods can be divided into two main categories: (1) methods based …

… EMG pattern recognition system using ANFIS as classifier with a real-time learning method.
… based decision making systems by combining the advantage of artificial neural network with …

… pattern recognition techniques for the classification of EMG signals. Recent advances in
computer technology have made automated EMG … i) an artificial neural network technique based …

… EMG system was developed with the idea of assembling it in an embedded device in the
near future. The EMG pattern recognition … technique to optimize an EMG pattern recognition …

… This section presents the state of the art methods used in the recognition of recurring
patterns in EMG data streams. … EMG pattern recognition based on artificial intelligence …

… presents three supervised methods to recognize actions from athletes using EMG and
positional … Six EMG channels collected physiological data, specifically right and left quadriceps, …

… artificial neural network (ANN) is founded and trained by the training dataset. A test method
is used in which the gesture will be recognized … Unlike other methods, our method starts …

… signal processing techniques and suitable machine learning … led to the development of
intelligent EMG-PR prostheses … of the existing intelligent EMG-PR based control method and …

… signal classification is an artificial neural network (ANN). An ANN is easily trainable and has
the capability of modelling both linear and non-linear data [49]. The SVM classifier, due to its …