Enhancing Visual-Guided Motor Imagery Performance via Sensory Threshold Somatosensory Electrical Stimulation Training-Reference-Cited by-同舟云学术

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Enhancing Visual-Guided Motor Imagery Performance via Sensory Threshold Somatosensory Electrical Stimulation Training

Published:2023-02 Issue:2 Volume:70 Page:756-765
ISSN:0018-9294
Container-title:IEEE Transactions on Biomedical Engineering
language:
Short-container-title:IEEE Trans. Biomed. Eng.

Author:

Zhang Lei¹^ORCID,Chen Long²^ORCID,Wang Zhongpeng³^ORCID,Zhang Xin³^ORCID,Liu Xiuyun³^ORCID,Ming Dong²^ORCID

Affiliation:

1. Academy of Medical Engineering and Translational Medicine, Tianjin University, China

2. Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China

3. College of Precision Instruments and Optoelectronics Engineering, Tianjin University, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering

Link

http://xplorestaging.ieee.org/ielx7/10/10021907/09869324.pdf?arnumber=9869324

Reference44 articles.

1. Reinforcement learning of self-regulated sensorimotor β-oscillations improves motor performance

2. Alpha, beta and gamma electrocorticographic rhythms in somatosensory, motor, premotor and prefrontal cortical areas differ in movement execution and observation in humans

3. FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data

4. Temporal Expectation Modulates the Cortical Dynamics of Short-Term Memory

5. Better than random: A closer look on BCI results;mueller-putz;Int J Bioelectromagn,2008

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1. Distinct and additive effects of visual and vibratory feedback for motor rehabilitation: an EEG study in healthy subjects;Journal of NeuroEngineering and Rehabilitation;2024-09-12

2. Event-Related EEG Desynchronization Reveals Enhanced Motor Imagery From the Third Person Perspective by Manipulating Sense of Body Ownership With Virtual Reality for Stroke Patients;IEEE Transactions on Neural Systems and Rehabilitation Engineering;2024

3. A Decoding Method Using Riemannian Local Linear Feature Construction for a Lower-Limb Motor Imagery Brain–Computer Interface System;Electronics;2023-11-18

4. Editorial: Advances in bioelectronics and stimulation strategies for next generation neuroprosthetics;Frontiers in Neuroscience;2023-01-10

5. Enhancing Motor Imagery Performance by Antiphasic 10 Hz Transcranial Alternating Current Stimulation;IEEE Transactions on Neural Systems and Rehabilitation Engineering;2023

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