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...

INTRODUCTION The surface electromyogram (EMG) is a highly complex, structured signal. It contains a wealth of information on both the state of the muscle and on the central nervous system control patterns that govern its activation. Identifying the information that can be extracted reliably from the EMG signal and determining the optimal recording and analysis methods to achieve this, remains a...

The effect of subcutaneous fat on myoelectric signal amplitude and cross-talk was studied using finite element (FE) models of electromyogram (EMG) signal propagation. A FE model of the upper arm consisted of skin, fat, muscle and bone tissues in concentric layers. Single muscle fibre action potentials were simulated for muscle fibres at a variety of depths and combined to simulate surface EMG i...

The objective of this work is to design and construct a low cost Electromyogram (EMG) and Electrooculogram (EOG) signal conditioning system for assistive device applications. The proposed circuit is designed for capturing surface EMG signal and EOG signal available on the surface of the human skin. This paper describes the system containing two units: signal detection unit and signal conditioni...

Motor unit action potentials (MUAPs) from motoneurons are transmitted to muscles through end-plates and then propagated to the tendons. These bioelectrical signals are detected via electromyography (EMG), which is performed using electrodes. The electrodes used in EMG are primarily surface electrodes and inserted (wire or needle) electrodes, of which surface and wire electrodes are mainly used ...

This paper presents our recent advances in speech recognition based on surface electromyography (EMG). This technology allows for Silent Speech Interfaces since EMG captures the electrical potentials of the human articulatory muscles rather than the acoustic speech signal. Our earlier experiments have shown that the EMG signal is greatly impacted by the mode of speaking. In this study we extend...

the purpose of this study was to estimate the torque from high‑density surface electromyography signals of biceps brachii, brachioradialis, and the medial and lateral heads of triceps brachii muscles during moderate‑to‑high isometric elbow flexion‑extension. the elbow torque was estimated in two following steps: first, surface electromyography (emg) amplitudes were estimated using principal com...

During isometric contractions of increasing strength, motor units (MUs) are recruited by the central nervous system in an orderly manner starting with the smallest, with muscle fibers that usually show the lowest conduction velocity (CV). Theory predicts that the higher the velocity of propagation of the action potential, the higher the power at high frequencies of the detected surface signal. ...