Analysis and Comparison of Features and Algorithms to Classify Shoulder Movements From sEMG Signals-Reference-Cited by-同舟云学术

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Analysis and Comparison of Features and Algorithms to Classify Shoulder Movements From sEMG Signals

Published:2018-05-01 Issue:9 Volume:18 Page:3714-3721
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Rivela Diletta,Scannella Alessia^ORCID,Pavan Esteban E.^ORCID,Frigo Carlo A.^ORCID,Belluco Paolo^ORCID,Gini Giuseppina^ORCID

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/8334013/08309375.pdf?arnumber=8309375

Cited by 20 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. On the Decoding of Shoulder Joint Intent of Motion From Transient EMG: Feature Evaluation and Classification;IEEE Transactions on Medical Robotics and Bionics;2023-11

2. Monitoring Scapular Kinematics through Wearable Magneto-Inertial Measurement Units: State of the Art and New Frontiers;Sensors;2023-08-04

3. Mechanomyography Signal Pattern Recognition of Knee and Ankle Movements Using Swarm Intelligence Algorithm-Based Feature Selection Methods;Sensors;2023-08-04

4. Decoding transient sEMG data for intent motion recognition in transhumeral amputees;Biomedical Signal Processing and Control;2023-08

5. Canonical Correlation Analysis of Transient EMG Data for Multi-User Motion Intent Detection;2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS);2023-06

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