[1]ZHANG Yi,YIN Chunlin,CAI Jun.On a hybrid electroencephalograph and visual information intelligentwheelchair human-machine interactive system[J].CAAI Transactions on Intelligent Systems,2016,11(5):648-654.[doi:10.11992/tis.201511004]
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On a hybrid electroencephalograph and visual information intelligentwheelchair human-machine interactive system

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 11 Number of periods: 2016 5 Page number: 648-654 Column: 学术论文—智能系统 Public date: 2016-11-01
Title:
On a hybrid electroencephalograph and visual information intelligentwheelchair human-machine interactive system
Author(s):
ZHANG Yi;  YIN Chunlin;  CAI Jun
Information Accessibility Engineering R & D Center, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
Keywords:
EEG; visual information; sample updated; human-machine interaction
CLC:
TP242.6
DOI:
10.11992/tis.201511004
Abstract:
To address error recognition problems created by mental fatigue when a human subject partakes in a single motor imager process for a long period of time, a visual information assisted EEG (electroencephalograph) human-machine interactive control system was proposed. The system produces a new sample updated strategy, with the‘state’of the eyes being recognized by the improved Adaboost algorithm in real-time and the recognition result being used to decide which EEG signal to update as the model parameter for human-machine interaction. An experiment on controlling an intelligent wheelchair off a fixed trajectory with a‘8’glyph was undertaken. The results show that visual information is adopted effectively by the intelligent wheelchair users to avoid the fatique-related error recognition problem with good levels of efficiency; thus proving that the interactive method is feasible.
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