Task-Oriented Muscle Synergy Extraction Using An Autoencoder-Based Neural Model
The growing interest in wearable robots opens the challenge for developing intuitive and natural control strategies. Among several human–machine interaction approaches, myoelectric control consists of decoding the motor intention from muscular activity (or EMG signals) with the aim of driving prosth...
Main Authors: | Domenico Buongiorno, Giacomo Donato Cascarano, Cristian Camardella, Irio De Feudis, Antonio Frisoli, Vitoantonio Bevilacqua |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-04-01
|
Series: | Information |
Subjects: | |
Online Access: | https://www.mdpi.com/2078-2489/11/4/219 |
Similar Items
-
Muscle synergies in joystick manipulation
by: Liming Cai, et al.
Published: (2023-10-01) -
Continuous Estimation of Finger and Wrist Joint Angles Using a Muscle Synergy Based Musculoskeletal Model
by: Zixun He, et al.
Published: (2022-04-01) -
A Neuromechanical Model-Based Strategy to Estimate the Operator’s Payload in Industrial Lifting Tasks
by: Emanuele Feola, et al.
Published: (2023-01-01) -
The Number and Structure of Muscle Synergies Depend on the Number of Recorded Muscles: A Pilot Simulation Study with OpenSim
by: Cristina Brambilla, et al.
Published: (2022-11-01) -
Continuous Intention Prediction of Lifting Motions Using EMG-Based CNN-LSTM
by: Min-Seong Gwon, et al.
Published: (2024-01-01)