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🏛️國立陽明交通大學機構典藏

Author: search.filters.author.Duann, Jeng-RenSubject: search.filters.subject.Independent component analysis (ICA)

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    Detecting Frontal EEG Activities with Forehead Electrodes
    (2009)
    Duann, Jeng-Ren
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    Chen, Po-Chuan
    ;
    Ko, Li-Wei
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    Huang, Ruey-Song
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    Jung, Tzyy-Ping
    This study demonstrates the acquisitions of EEG signals from non-hairy forehead sites and tested the feasibility of using the forehead EEG in detecting drowsiness-related brain activities. A custom-made 15-channel forehead EEG-electrode patch and 28 scalp electrodes placed according to the International 10-20 system were used to simultaneously record EEG signals from the forehead and whole-head regions, respectively. A total of five Subjects were instructed to perform a night-time long-haul driving task for all hour in a virtual-reality based driving simulator comprising a real car mounted oil a 6 degree-of-freedom Steward motion platform and a immersive VR environment with 360 degree projection scenes. Separate independent component analyses were applied to the forehead and whole-head EEG data for each individual subject. For the whole-head independent component (IC) set, the frontal central midline (FCM) IC with an equivalent dipole source located in the interior cingulate cortex was selected for further analysis. For the forehead IC set, the IC with its theta power changes highly correlated with Subject\'s driving performance was selected. The EEG power changes of the selected forehead ICs were then used to predict driving performance based on a linear regression model. The results of this study showed that it is feasible to accurately estimate quantitatively the changing level of driving performance using the EEG features obtained from the forehead non-hairy channels, and the estimation accuracy was comparable to that using the EEG features of the whole-head recordings.
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    Spatial and temporal EEG dynamics of motion sickness
    (2010-02-01)
    Chen, Yu-Chieh
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    Duann, Jeng-Ren
    ;
    Chuang, Shang-Wen
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    Lin, Chun-Ling
    ;
    Ko, Li-Wei
    This study investigates motion-sickness-related brain responses using a VR-based driving simulator oil a motion platform with six degrees of freedom, which provides both visual and vestibular stimulations to induce motion sickness in a manner that is close to that in daily life. Subjects' brain dynamics associated with motion sickness were measured using a 32-channel EEG system. Their degree of motion sickness was simultaneously and continuously reported using an onsite joystick, providing non-stop behavioral references to the recorded EEG changes The acquired EEG signals were parsed by independent component analysis (ICA) into maximally independent processes. The decomposition enables the brain dynamics that are induced by the motion of the platform and motion sickness to be disassociated. Five MS-related brain processes with equivalent dipoles located in the left motor, the parietal. the right motor, the occipital and the occipital midline areas were consistently identified across all subjects. The parietal and motor components exhibited significant alpha power suppression in response to vestibular stimuli, while the occipital components exhibited MS-related power augmentation in mainly theta and delta bands: the occipital midline components exhibited a broadband power increase Further, time series cross-correlation analysis was employed to evaluate relationships between the spectral changes associated with different brain processes and the degree of motion sickness According to our results, it is suggested both visual and vestibular stimulations should be used to induce motion sickness in brain dynamic studies (C) 2009 Elsevier Inc. All rights reserved.