Utilizing Gramian Angular Fields and Convolution Neural Networks in Flex Sensors Glove for Human–Computer Interaction-Reference-Cited by-同舟云学术

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Utilizing Gramian Angular Fields and Convolution Neural Networks in Flex Sensors Glove for Human–Computer Interaction

Published:2024-08 Issue:4 Volume:54 Page:475-483
ISSN:2168-2291
Container-title:IEEE Transactions on Human-Machine Systems
language:
Short-container-title:IEEE Trans. Human-Mach. Syst.

Author:

Chansri Chana¹^ORCID,Srinonchat Jakkree¹^ORCID

Affiliation:

1. Rajamangala University of Technology Thanyaburi, Khlong Hok, Thailand

Funder

NSRF via the Program Management Unit for Human Resources and Institutional Development

Research and Innovation

National Research Council of Thailand

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6221037/10604683/10551549.pdf?arnumber=10551549

Reference32 articles.

1. Knit Band Sensor for Myoelectric Control of Surface EMG-Based Prosthetic Hand

2. An sEMG-Based Human–Robot Interface for Robotic Hands Using Machine Learning and Synergies

3. A novel data glove using inertial and magnetic sensors for motion capture and robotic arm-hand teleoperation

4. A Shared Autonomy Reconfigurable Control Framework for Telemanipulation of Multi-Arm Systems

5. GESTO: A Glove for Enhanced Sensing and Touching Based on Inertial and Magnetic Sensors for Hand Tracking and Cutaneous Feedback

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1. MRSAPose: Multi-level routing sparse attention for multi-person pose estimation;Expert Systems with Applications;2024-12

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