Deep stacked support matrix machine based representation learning for motor imagery EEG classification-Reference-Cited by-同舟云学术

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Deep stacked support matrix machine based representation learning for motor imagery EEG classification

Published:2020-09 Issue: Volume:193 Page:105466
ISSN:0169-2607
Container-title:Computer Methods and Programs in Biomedicine
language:en
Short-container-title:Computer Methods and Programs in Biomedicine

Author:

Hang Wenlong,Feng Wei,Liang Shuang,Wang Qiong,Liu Xuejun,Choi Kup-Sze

Funder

Key R & D programs

National Natural Science Foundation of China

Natural Science Foundation of the Higher Education Institutions of Jiangsu Province

CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems

Hong Kong Research Grants Council

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications,Software

Reference43 articles.

1. A review of disability EEG based wheelchair control system: Coherent taxonomy, open challenges and recommendations;Al-Qaysi;Comput. Methods Programs Biomed.,2018

2. Temporal classification of multichannel near-infrared spectroscopy signals of motor imagery for developing a brain–computer interface;Sitaram;Neuroimage,2007

3. A large clinical study on the ability of stroke patients to use an EEG-based motor imagery brain-computer interface;Ang;Clin. EEG Neurosci.,2011

4. Brain–computer interfaces: communication and restoration of movement in paralysis;Birbaumer;J. Physiol.,2007

5. EEG correlates of video game experience and user profile in motor-imagery-based brain–computer interaction;Vourvopoulos;Vis. Comput.,2017

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2. Optimal margin distribution matrix machine;Expert Systems with Applications;2024-04

3. Efficient space learning based on kernel trick and dimension reduction technique for multichannel motor imagery EEG signals classification;Neural Computing and Applications;2023-10-14

4. MBGA-Net: A multi-branch graph adaptive network for individualized motor imagery EEG classification;Computer Methods and Programs in Biomedicine;2023-10

5. Deep extreme learning machine with knowledge augmentation for EEG seizure signal recognition;Frontiers in Neuroinformatics;2023-08-24

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