A fundamental issue in motor control is how to determine the task goals for a given behavior. Here, we address this question by separately identifying the musculoskeletal and feedback components of the human postural control loop. Eighteen subjects were perturbed by two mechanical perturbations (gentle pulling from behind at waist and shoulder levels) and one sensory perturbation (movement of a...

This paper presents a developed tool capable of decomposing electromyographic signals (EMG) named EMG Decomposition. The main aim of this software is to extract and to visualize motor unit action potentials (MUAPs) extracted from EMG signals during a muscular contraction. The identification and clustering of MUAPs that show similar features is most important for the definition of such cluster s...

Wavelet analysis is often very effective because it provides a simple approach for dealing with local aspects of a signal. Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development, and modern human computer interaction. EMG signals acquired from muscles require advanced methods for detection, decomposition, processing, and classi...

---------------------------------------------------------------------***--------------------------------------------------------------------Abstract Electromyography (EMG) is an electrodiagnostic technique for evaluating and recording the electrical activity produced by skeletal muscles. EMG is performed using an instrument called an Electromyograph, to produce a record called an Electromyogram...

Background: Electromyographic (EMG) signals obtained from a contracted muscle contain valuable information on its activity and health status. Much of this information lies in motor unit potentials (MUPs) of its motor units (MUs), collected during the muscle contraction. Hence, accurate estimation of a MUP template for each MU is crucial. Objective: To investigate the possibility of improv...

Electromyographic (EMG) signals are used as rich information sources for control of intelligent prosthetics. For efficient classification the machine learning algorithms used should allow the nonlinear nature of the multi class problem. For generalized application they should have the analytical ability to systematically tackle the problem in hand. To meet these requirements a pair-wise Linear ...

This paper presents a developed tool capable of decomposing electromyographic signals (EMG) named EMG Decomposition. The main aim of this software is to extract and to visualize motor unit action potentials extracted from EMG signals during a muscular contraction. The results obtained from the tool have application in the study of the behavior of the central nervous system and in the diagnosis ...

We aimed to determine the neurophysiological pattern that is associated with development of musculoskeletal pain induced by biomechanical constraints. Twelve (12) young healthy volunteers (two females) performed two experimental realistic manual tasks for 30 min each: (1) high risk and (2) low development. During tasks, synchronized electroencephalographic (EEG) electromyography (EMG) signals d...

A novel approach is presented for the analysis of surface electromyogram (EMG) morphology in Parkinson's disease (PD). The method is based on histogram and crossing rate (CR) analysis of the EMG signal. In the method, histograms and CR values are used as high-dimensional feature vectors. The dimensionality of them is then reduced using the Karhunen-Loève transform (KLT). Finally, the discrimina...

Despite the many reviews and research papers on the limitations of surface electromyography (EMG), there are relatively few that address this issue by considering dynamic contractions and specifically from the point of view of muscle coordination. Nevertheless, whether muscle coordination can be precisely studied using surface EMG signals is still a matter of discussion in the scientific commun...