Enhanced EMG-Based Hand Gesture Classification in Real-World Scenarios: Mitigating Dynamic Factors With Tempo-Spatial Wavelet Transform and Deep Learning-Reference-Cited by-同舟云学术

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Enhanced EMG-Based Hand Gesture Classification in Real-World Scenarios: Mitigating Dynamic Factors With Tempo-Spatial Wavelet Transform and Deep Learning

Published:2024-08 Issue:3 Volume:6 Page:1202-1211
ISSN:2576-3202
Container-title:IEEE Transactions on Medical Robotics and Bionics
language:
Short-container-title:IEEE Trans. Med. Robot. Bionics

Author:

Rani Parul¹^ORCID,Pancholi Sidharth²^ORCID,Shaw Vikash¹^ORCID,Atzori Manfredo³^ORCID,Kumar Sanjeev¹^ORCID

Affiliation:

1. Academy of Scientific and Innovative Research, Ghaziabad, India

2. Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA

3. Information Systems Institute, University of Applied Sciences Western Switzerland (HES-SO Valais), Sierre, Switzerland

Funder

Council of Scientific and Industrial Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/8253409/10631864/10547182.pdf?arnumber=10547182

Reference30 articles.

1. Comparing EMG-Based Human-Machine Interfaces for Estimating Continuous, Coordinated Movements

2. A Hierarchical Hand Gesture Recognition Framework for Sports Referee Training-Based EMG and Accelerometer Sensors

3. A Neuro-Fuzzy Fatigue-Tracking and Classification System for Wheelchair Users

4. Position-Independent Decoding of Movement Intention for Proportional Myoelectric Interfaces

5. Time Derivative Moments Based Feature Extraction Approach for Recognition of Upper Limb Motions Using EMG

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