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Brain-computer interface (BCI) 1

Chinese speller 1

Electroencephalography (EEG) 1

English speller 1

active orthosis 1

electroencephalography 1

gait rehabilitation 1

surface electromyography 1

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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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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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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 external environment by means of their EEG signals, without relying on the brain’s usual output pathways such as muscles. A popular application for EEGs is the EEG-based speller, which translates EEG signals into intentions to spell particular words, thus benefiting those suffering from severe disabilities, such as amyotrophic lateral sclerosis. Although the EEG-based English speller (EEGES) has been widely studied in recent years, few studies have focused on the EEG-based Chinese speller (EEGCS). The EEGCS is more difficult to develop than the EEGES, because the English alphabet contains only 26 letters. By contrast, Chinese contains more than 11 000 logographic characters. The goal of this paper is to survey the literature on EEGCS systems. First, the taxonomy of current EEGCS systems is discussed to get the gist of the paper. Then, a common framework unifying the current EEGCS and EEGES systems is proposed, in which the concept of EEG-based choice acts as a core component. In addition, a variety of current EEGCS systems are investigated and discussed to highlight the advances, current problems, and future directions for EEGCS.

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

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Title Author Date Type Operation

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

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

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