sEMG-Based Continuous Hand Action Prediction by Using Key State Transition and Model Pruning

sEMG-Based Continuous Hand Action Prediction by Using Key State Transition and Model Pruning

Conventional classification of hand motions and continuous joint angle estimation based on sEMG have been widely studied in recent years. The classification task focuses on discrete motion recognition and shows poor real-time performance, while continuous joint angle estimation evaluates the real-ti...

Full description

Bibliographic Details
Main Authors: Kaikui Zheng, Shuai Liu, Jinxing Yang, Metwalli Al-Selwi, Jun Li
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Sensors
Subjects:
sEMG
GMM-HMMs
key state transition
model pruning
continuous two-hand action prediction
sliding window
Online Access:https://www.mdpi.com/1424-8220/22/24/9949

Similar Items

Similar Items