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Journal Article 8

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2022 1

2021 2

2019 1

2018 1

2015 2

2011 1

Keywords

Electroencephalogram (EEG) 3

Brain-computer interface (BCI) 2

Attention mechanism 1

Chinese speller 1

Classification 1

Electroencephalography (EEG) 1

Electrooculogram (EOG) 1

Emotion recognition 1

English speller 1

Feature extraction 1

Improved common spatial pattern (B-CSP) 1

Motor imagery (MI) 1

Ocular artifacts 1

Personality traits 1

Spatial constraint independent component analysis based recursive least squares (SCICA-RLS) 1

active orthosis 1

brain computer interface 1

brain–computer interface 1

chronic stroke 1

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Electroencephalogram-based brain-computer interface for the Chinese spelling system: a survey None

Ming-hui SHI, Chang-le ZHOU, Jun XIE, Shao-zi LI, Qing-yang HONG, Min JIANG, Fei CHAO, Wei-feng REN, Xiang-qian LIU, Da-jun ZHOU, Tian-yu YANG

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 3,   Pages 423-436 doi: 10.1631/FITEE.1601509

Abstract: Electroencephalogram (EEG) based brain-computer interfaces allow users to communicate with the externalenvironment by means of their EEG signals, without relying on the brain’s usual output pathways suchA popular application for EEGs is the EEG-based speller, which translates EEG signals into intentionsAlthough the EEG-based English speller (EEGES) has been widely studied in recent years, few studies havefocused on the EEG-based Chinese speller (EEGCS).

Keywords： Brain-computer interface (BCI)     Electroencephalography (EEG)     Chinese speller     English speller    

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Classification of EEG-based single-trial motor imagery tasks using aB-CSP method forBCI Research Articles

Zhi-chuan TANG, Chao LI, Jian-feng WU, Peng-cheng LIU, Shi-wei CHENG

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 8,   Pages 1087-1098 doi: 10.1631/FITEE.1800083

Abstract: Classifying single-trial electroencephalogram (EEG) based motor imagery (MI) tasks is extensively usedHowever, the low signal-to-noise ratio and individual differences of EEG can affect the classificationthe features that can describe the maximum differences of two classes of MI are extracted from the EEGwhich are input into a back propagation neural network (BPNN) classifier to classify single-trial MI EEGThe results demonstrate that our proposed B-CSP method can classify EEG-based MI tasks effectively, and

Keywords： Electroencephalogram (EEG)     Motor imagery (MI)     Improved common spatial pattern (B-CSP)     Feature extraction    

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EEG-controlled functional electrical stimulation rehabilitation for chronic stroke: system design and

Frontiers of Medicine 2021, Volume 15, Issue 5,   Pages 740-749 doi: 10.1007/s11684-020-0794-5

Abstract: outcome measures during intervention were compared between groups, and the trends of ERD values based on EEG

Keywords： brain–computer interface     functional electrical stimulation     electroencephalogram     laterality coefficient     chronic stroke    

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Current Challenges for the Practical Application of Electroencephalography-Based Brain–Computer Interfaces

Minpeng Xu,  Feng He,  Tzyy-Ping Jung,  Xiaosong Gu,  Dong Ming

Engineering 2021, Volume 7, Issue 12,   Pages 1710-1712 doi: 10.1016/j.eng.2021.09.011

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EEG controlled neuromuscular electrical stimulation of the upper limb for stroke patients

Hock Guan TAN, Cheng Yap SHEE, Keng He KONG, Cuntai GUAN, Wei Tech ANG

Frontiers of Mechanical Engineering 2011, Volume 6, Issue 1,   Pages 71-81 doi: 10.1007/s11465-011-0207-1

Abstract: and the experiments to allow post-acute (<3 months) stroke patients to use electroencephalogram (EEGEEG was recorded while subjects performed motor imagery of their paretic limb, and then analyzed to determineAided by visual feedback, subjects then trained to regulate their -rhythm EEG to operate the BCI to trigger

Keywords： brain computer interface     neuromuscular electrical stimulation     stroke     musculoskeletal modeling    

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Design of active orthoses for a robotic gait rehabilitation system

A. C. VILLA-PARRA,L. BROCHE,D. DELISLE-RODRÍGUEZ,R. SAGARÓ,T. BASTOS,A. FRIZERA-NETO

Frontiers of Mechanical Engineering 2015, Volume 10, Issue 3,   Pages 242-254 doi: 10.1007/s11465-015-0350-1

Abstract:

An active orthosis (AO) is a robotic device that assists both human gait and rehabilitation therapy. This work proposes portable AOs, one for the knee joint and another for the ankle joint. Both AOs will be used to complete a robotic system that improves gait rehabilitation. The requirements for actuator selection, the biomechanical considerations during the AO design, the finite element method, and a control approach based on electroencephalographic and surface electromyographic signals are reviewed. This work contributes to the design of AOs for users with foot drop and knee flexion impairment. However, the potential of the proposed AOs to be part of a robotic gait rehabilitation system that improves the quality of life of stroke survivors requires further investigation.

Keywords： active orthosis     gait rehabilitation     electroencephalography     surface electromyography    

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A personality-guided affective brain–computer interface for implementation of emotional intelligence in machines Research Article

Shaojie LI, Wei LI, Zejian XING, Wenjie YUAN, Xiangyu WEI, Xiaowei ZHANG, Bin HU,zhangxw@lzu.edu.cn,bh@lzu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 8,   Pages 1158-1173 doi: 10.1631/FITEE.2100489

Abstract: the influence of on emotional response, it would be helpful to integrate personality information and EEGpersonality-guided attention neural network that can use personality information to learn effective EEGwe first use a convolutional neural network to extract rich temporal and regional representations of EEGFinally, attention-based long short-term memory is designed to explore the temporal dynamics of EEG signals

Keywords： Electroencephalogram (EEG)     Emotion recognition     Attention mechanism     Personality traits    

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Fast removal of ocular artifacts from electroencephalogram signals using spatial constraint independent component analysis based recursive least squares in brain-computer interface

Bang-hua YANG,Liang-fei HE,Lin LIN,Qian WANG

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 6,   Pages 486-496 doi: 10.1631/FITEE.1400299

Abstract: Ocular artifacts cause the main interfering signals within electroencephalogram (EEG) signal measurementselectrooculogram (EOG) can reduce ocular interference, but collecting EOG signals during a long-term EEGTo remove ocular artifacts from EEG in brain-computer interfaces (BCIs), a method named spatial constraintIn the first stage, independent component analysis (ICA) is used to decompose multiple EEG channels intoaccuracies of 3.3% and 12.6% higher than those of the standard ICA and raw EEG, respectively.

Keywords： Ocular artifacts     Electroencephalogram (EEG)     Electrooculogram (EOG)     Brain-computer interface (BCI)    

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Title Author Date Type Operation

Electroencephalogram-based brain-computer interface for the Chinese spelling system: a survey

Ming-hui SHI, Chang-le ZHOU, Jun XIE, Shao-zi LI, Qing-yang HONG, Min JIANG, Fei CHAO, Wei-feng REN, Xiang-qian LIU, Da-jun ZHOU, Tian-yu YANG

Journal Article

Classification of EEG-based single-trial motor imagery tasks using aB-CSP method forBCI

Zhi-chuan TANG, Chao LI, Jian-feng WU, Peng-cheng LIU, Shi-wei CHENG

Journal Article

EEG-controlled functional electrical stimulation rehabilitation for chronic stroke: system design and

Journal Article

Current Challenges for the Practical Application of Electroencephalography-Based Brain–Computer Interfaces

Minpeng Xu,  Feng He,  Tzyy-Ping Jung,  Xiaosong Gu,  Dong Ming

Journal Article

EEG controlled neuromuscular electrical stimulation of the upper limb for stroke patients

Hock Guan TAN, Cheng Yap SHEE, Keng He KONG, Cuntai GUAN, Wei Tech ANG

Journal Article

Design of active orthoses for a robotic gait rehabilitation system

A. C. VILLA-PARRA,L. BROCHE,D. DELISLE-RODRÍGUEZ,R. SAGARÓ,T. BASTOS,A. FRIZERA-NETO

Journal Article

A personality-guided affective brain–computer interface for implementation of emotional intelligence in machines

Shaojie LI, Wei LI, Zejian XING, Wenjie YUAN, Xiangyu WEI, Xiaowei ZHANG, Bin HU,zhangxw@lzu.edu.cn,bh@lzu.edu.cn

Journal Article

Fast removal of ocular artifacts from electroencephalogram signals using spatial constraint independent component analysis based recursive least squares in brain-computer interface

Bang-hua YANG,Liang-fei HE,Lin LIN,Qian WANG

Journal Article