A Long Short-Term Memory-Based Interconnected Architecture for Classification of Grasp Types Using Surface-Electromyography Signals

Article

Abstract: Reliable classification of grasp types from human limbs has become an important aspect used by appli

Palabras claves:

Bidirectional LSTM networks, biomedical signal processing, classification algorithms, Computer Architecture, deep learning, Electromyography, Feature Extraction, grasp types classification, Muscles, surface muscular signals, time series analysis

Autores:

Andres Erazo, Ko S.B.

Fuentes:

scopus