Phantom Movement Training Without Classifier Performance Feedback Improves Mobilization Ability While Maintaining EMG Pattern Classification-Reference-Cited by-同舟云学术

Phantom Movement Training Without Classifier Performance Feedback Improves Mobilization Ability While Maintaining EMG Pattern Classification

Published:2023-02 Issue:1 Volume:5 Page:133-142
ISSN:2576-3202
Container-title:IEEE Transactions on Medical Robotics and Bionics
language:
Short-container-title:IEEE Trans. Med. Robot. Bionics

Author:

Rossel Olivier¹,Chateaux Manon²^ORCID,Jarrassé Nathanaël³^ORCID,Vérité Fabien³,Touillet Amélie⁴,Nicol Caroline²^ORCID,Paysant Jean⁴,De Graaf Jozina B.²^ORCID

Affiliation:

1. Institute of Movement Sciences, Aix Marseille Université, CNRS ISM, Marseille, France

2. Aix-Marseille University, CNRS, ISM,, Marseille, France

3. CNRS, ISIR/INSERM, Sorbonne University, Paris, France

4. IRR, UGECAM Nord-Est, Nancy, France

Funder

Region Provence-Alpes-Côte d’Azur

French National Center of Scientific Research

French National Agency of Research

A*Midex International

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Human-Computer Interaction,Biomedical Engineering

Link

http://xplorestaging.ieee.org/ielx7/8253409/10051132/10024109.pdf?arnumber=10024109

Reference39 articles.

1. Phantom-Mobility-Based Prosthesis Control in Transhumeral Amputees Without Surgical Reinnervation: A Preliminary Study

2. User adaptation in long-term, open-loop myoelectric training: implications for EMG pattern recognition in prosthesis control

3. Voluntary phantom hand and finger movements in transhumeral amputees could be used to naturally control polydigital prostheses;jarrasse;arXiv 1904 11702,2019

4. Feature reduction and selection for EMG signal classification

5. The Motor Cortex and Its Role in Phantom Limb Phenomena

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