Cargando…
An Electromyographic-driven Musculoskeletal Torque Model using Neuro-Fuzzy System Identification: A Case Study
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 fol...
Autores principales: | Jafari, Zohreh, Edrisi, Mehdi, Marateb, Hamid Reza |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Medknow Publications & Media Pvt Ltd
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4236802/ https://www.ncbi.nlm.nih.gov/pubmed/25426427 |
Ejemplares similares
-
Designing a Low-noise, High-resolution, and Portable Four Channel Acquisition System for Recording Surface Electromyographic Signal
por: Pashaei, Akbar, et al.
Publicado: (2015) -
A noninvasive method for coronary artery diseases diagnosis using a clinically-interpretable fuzzy rule-based system
por: Marateb, Hamid Reza, et al.
Publicado: (2015) -
Fuzzy jump wavelet neural network based on rule induction for dynamic nonlinear system identification with real data applications
por: Kharazihai Isfahani, Mohsen, et al.
Publicado: (2019) -
A real-time and convex model for the estimation of muscle force from surface electromyographic signals in the upper and lower limbs
por: Shirzadi, Mehdi, et al.
Publicado: (2023) -
Kernel Density Estimation of Electromyographic Signals and Ensemble Learning for Highly Accurate Classification of a Large Set of Hand/Wrist Motions
por: Ghaderi, Parviz, et al.
Publicado: (2022)