This paper emphasizes on the hand movement recognition using artificial neural network
(ANN). It shows the methodology that analyses and classifies the electromyography (EMG) …

This work presents a comparative study between dimensionality reduction and feature
selection to classification problem for six hand gestures by sEMG signal. The classified …

This work presented a method to automatic classify six hand and wrist gestures (wrist
flexion, wrist extension, wrist flexion to left, wrist extension to right, supination, and …

Electromyography (EMG) employs widespread usage of rehabilitation robotics. EMG informs
about the maximum capabilities of muscles and allows comparisons between different tasks …

Myoelectric control prostheses fingers are a popular developing clinical option that offers an
amputee person to control their artificial fingers by recognizing the contacting muscle …

Purpose Some factors such as gender, age, physical fitness, and manual dominance are
relevant and can influence the recognition of movement patterns using electromyography …

Using nonlinear signal processing methods is critical in processing biological signals due to
their nonlinear dynamics. Recurrence plots are one of these nonlinear methods that provide …

Este artículo presenta el desarrollo de BioMePro, una herramienta de software para el
Procesamiento de Muestras de Electromiografía (EMG) superficial, implementado en JAVA …