The purpose of this article is to provide an overview of current applications of artificial neural
networks in the area of clinical biomechanics. The body of literature on artificial neural …

Support vector machine (SVM) is an extensively used machine learning method with many
biomedical signal classification applications. In this study, a novel PSO-SVM model has …

A novel approach to the control of a multifunction prosthesis based on the classification of
myoelectric patterns is described. It is shown that the myoelectric signal exhibits a …

This authoritative handbook reveals the connections between bioinspired techniques and
the development of solutions to problems that arise in diverse problem domains. It provides …

Different approaches have been applied for quantitative analysis of EMG signals. This study
introduces the effect of Multiscale Principal Component Analysis (MSPCA) denoising …

As in many other fields, biomedical engineers benefit from the use of computational
intelligence (CI) tools to solve complex and non-linear problems. The benefits could be even …

In this paper, a novel bacterial foraging algorithm (BFA)-Gaussian support vector classifier
machine (GSVCM) model was proposed to improve the fatigue classification accuracy of …

Over the past three decades, various computational methods have been developed for
electroencephalographic (EEG) signal analysis. In addition, methods based on statistical …

Support vector machines (SVMs) have been widely used in many pattern recognition
problems. Generally, the performance of SVM classifiers is affected by the selection of the …

In this study, a novel BF–PSO–FSVCM model has been proposed to identify the fatigue
status of the electromyography (EMG) signal. To improve the classifier accuracy of fuzzy …