Browsing by Author "Chuang, Shang-Wen"

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Co-modulatory spectral changes in independent brain processes are correlated with task performance
(2012-09-01)
Chuang, Shang-Wen
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Ko, Li-Wei
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Lin, Yuan-Pin
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Huang, Ruey-Song
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Jung, Tzyy-Ping
"This study investigates the independent modulators that mediate the power spectra of electrophysiological processes, measured by electroencephalogram (EEG), in a sustained-attention experiment. EEG and behavioral data were collected during 1-2 hour virtual-reality based driving experiments in which subjects were instructed to maintain their cruising position and compensate for randomly induced drift using the steering wheel. Independent component analysis (ICA) applied to 30-channel EEG data separated the recorded EEG signals into a sum of maximally temporally independent components (ICs) for each of 30 subjects. Logarithmic spectra of resultant IC activities were then decomposed by principal component analysis, followed by ICA, to find spectrally fixed and temporally independent modulators (IM). Across subjects, the spectral ICA consistently found four performance-related independent modulators: delta, delta-theta, alpha, and beta modulators that multiplicatively affected the spectra of spatially distinct IC processes when the participants experienced waves of alternating alertness and drowsiness during long-hour simulated driving. The activation of the delta-theta modulator increased monotonically as subjects' task performances decreased. Furthermore, the time courses of the theta-beta modulator were highly correlated with concurrent changes in driving errors across subjects (r = 0.77 +/- 0.13). (c) 2012 Elsevier Inc. All rights reserved."
EEG Alpha and Gamma Modulators Mediate Motion Sickness-Related Spectral Responses
(2016-03)
Chuang, Shang-Wen
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Chuang, Chun-Hsiang
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Yu, Yi-Hsin
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King, Jung-Tai
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Lin, Chin-Teng
Motion sickness (MS) is a common experience of travelers. To provide insights into brain dynamics associated with MS, this study recruited 19 subjects to participate in an electroencephalogram (EEG) experiment in a virtual-reality driving environment. When riding on consecutive winding roads, subjects experienced postural instability and sensory conflict between visual and vestibular stimuli. Meanwhile, subjects rated their level of MS on a six-point scale. Independent component analysis (ICA) was used to separate the filtered EEG signals into maximally temporally independent components (ICs). Then, reduced logarithmic spectra of ICs of interest, using principal component analysis, were decomposed by ICA again to find spectrally fixed and temporally independent modulators (IMs). Results demonstrated that a higher degree of MS accompanied increased activation of alpha (r = 0.421) and gamma (r = 0.478) IMs across remote-independent brain processes, covering motor, parietal and occipital areas. This co-modulatory spectral change in alpha and gamma bands revealed the neurophysiological demand to regulate conflicts among multi-modal sensory systems during MS.
EEG effects of motion sickness induced in a dynamic virtual reality environment
(2007)
Lin, Chin-Teng
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Chuang, Shang-Wen
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Chen, Yu-Chieh
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Ko, Li-Wei
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Liang, Sheng-Fu
The Electroencephalogram (EEG) dynamics which relate to motion sickness are studied in this paper. Instead of providing visual or motion stimuli to the subjects to induce motion sickness, we employed a dynamic virtual-reality (VR) environment in our research. The environment consisted of a 3D surrounding VR scene and a motion platform providing a realistic situation. This environment provided the advantages of safety, low cost, and the realistic stimuli to induce motion sickness. The Motion Sickness Questionnaire (MSQ) was used to assess the sickness level, and the EEG effects on the subjects with high sickness levels were investigated using the independent component analysis (ICA). The fake-epoch extraction was then applied to the nausea-related independent components. Finally we employed the Event-Related Spectral Perturbation (ERSP) technology on the fake-epochs in order to determine the EEG dynamics during motion sickness. The experimental results show that most subjects experienced an 8-10 Hz power increase to their motion sickness-related phenomena in the parietal and motor areas. Moreover, some subjects experienced an EEG power increase of 18-20 Hz in their synchronized responses recorded in the same areas. The motion sickness-related effects and regions can be successfully obtained from our experimental results.
EEG-based Evaluation System for Motion Sickness Estimation
(2011)
Wei, Chun-Shu
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Ko, Li-Wei
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Chuang, Shang-Wen
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Jung, Tzyy-Ping
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Lin, Chin-Teng
Motion sickness is a common symptom which occurs when the brain receives conflicting sensory information. Although many motion sickness-related biomarkers have been identified, estimating humans' motion sickness level (MSL) remains a challenge in operational environments. Traditionally, questionnaire and physical check are the common ways to passively evaluate subject's sickness level. This study proposes a physiology-based estimation system that can automatically assess subject's motion-sickness level in operational environments. Our previous study showed that increases in self-reported MSL in a Virtual-reality based driving experiment on a motion platform were accompanied by elevated alpha (8-12Hz) power most prominently in the occipital midline electroencephalogram (EEG). This study explores the feasibility of an automatic MSL estimation based on spontaneous EEG spectrum. To this end, this study employed three different estimators: 1) Linear regression (LR), 2) Radial basis function neural network (RBFNN), and 3) Support vector regression (SVR). The results of this study showed that SVR outperformed LR and RBFNN in estimating MSL from EEG spectrum. The averaged accuracy of MSL estimation by SVR was 86.92 +/- 6.09% across 6 subjects. This demonstration could lead to a practical system for noninvasive monitoring of the motion sickness in real-world environments.
Genetic Feature Selection in EEG-Based Motion Sickness Estimation
(2011)
Wei, Chun-Shu
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Ko, Li-Wei
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Chuang, Shang-Wen
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Jung, Tzyy-Ping
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Lin, Chin-Teng
Motion sickness is a common symptom that occurs when the brain receives conflicting information about the sensation of movement. Many motion sickness biomarkers have been identified, and electroencephalogram (EEG)-based motion sickness level estimation was found feasible in our previous study. This study employs genetic feature selection to find a subset of EEG features that can further improve estimation performance over the correlation-based method reported in the previous studies. The features selected by genetic feature selection were very different from those obtained by correlation analysis. Results of this study demonstrate that genetic feature selection is a very effective method to optimize the estimation of motion-sickness level. This demonstration could lead to a practical system for noninvasive monitoring of the motion sickness of individuals in real-world environments.
Implementation of a Motion Sickness Evaluation System Based on EEG Spectrum Analysis
(2011)
Wei, Chun-Shu
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Chuang, Shang-Wen
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Wang, Wan-Ru
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Ko, Li-Wei
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Jung, Tzyy-Ping
Motion sickness is a normal response to real, perceived, or even anticipated movement. People tend to get motion sickness on a moving boat, train, airplane, car, or amusement park rides. Motion sickness occurs when the body, the inner ear, and the eyes send conflicting signals to the brain. Sensory conflict theory that came about in the 1970's has become the most widely accepted theorem of motion-sickness among scientists [1]. The theory proposed that the conflict between the incoming sensory inputs could induce motion-sickness. However, some new research studies have appeared to tackle the issue of the vestibular function in central nervous system (CNS). In the previous human subject studies, researchers attempt to confirm the brain areas involved in the conflict in multi-modal sensory systems by means of clinical or anatomical methods. Our past studies had investigated the EEG activities correlated with motion sickness in a virtual-reality based driving simulator. We found that the parietal, motor, occipital brain regions exhibited significant EEG power changes in response to vestibular and visual stimuli. Based on these experimental results, we attempt to implement an EEG-based evaluation system to estimate subject's motion sickness level upon the major EEG power spectra from these motion sickness related brain area in this study. The evaluation system can be applied to early detect the subject's motion sickness level and prevent the uncomfortable syndromes occurred in advance in our daily life.
Motion-Sickness Related Brain Areas and EEG Power Activates
(2009)
Chen, Yu-Chieh
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Duann, Jeng-Ren
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Lin, Chun-Ling
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Chuang, Shang-Wen
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Jung, Tzyy-Ping
This study investigates electroencephalographic (EEG) correlates of motion sickness in a virtual-reality based driving simulator. The driving simulator comprised an actual automobile mounted on a Stewart motion platform with six degrees of freedom, providing both visual and vestibular stimulations to induce motion-sickness in a manner that is close to that in daily life. EEG data were acquired at a sampling rate of 500 Hz using a 32-channel EEG system. The acquired EEG signals were analyzed using independent component analysis (ICA) and time-frequency analysis to assess EEG correlates of motion sickness. Subject's degree of motion-sickness was simultaneously and continuously reported using an onsite joystick, providing non-stop psychophysical references to the recorded EEG changes. Five Motion-sickness 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. These components exhibited distinct spectral suppressions or augmentation in motion sickness. The results of this study could lead to a practical human-machine interface for noninvasive monitoring of motion sickness of drivers or passengers in real-world environments.
Self-adjustments may account for the contradictory correlations between HRV and motion-sickness severity
(2013-01-01)
Lin, Chun-Ling
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Jung, Tzyy-Ping
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Chuang, Shang-Wen
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Duann, Jeng-Ren
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Lin, Chin-Teng
This study investigates the relationship between heart rate variability (HRV) and the level of motion sickness (MS) induced by simulated tunnel driving. The HRV indices, normalized low frequency (NLF, 0.04-0.15 Hz), normalized high frequency (NHF, 0.15-0.4 Hz), and LF/HF ratio were correlated with the subjectively and continuously rated MS levels of 20 participants. The experimental results showed that for 13 of the subjects, the MS levels positively correlated with the NLF and the LF/HF ratio and negatively correlated with the NHF. The remaining seven subjects had negative correlations between the MS levels and the NLF and the LF/HF ratio and a positive correlation between the MS levels and the NHF. To clarify this contradiction, this study also inspected the effects of subjects' self-adjustments on the correlations between the MS levels and the HRV indices and showed that the variations in the relationship might be attributed to the subjects' self-adjustments, which they used to relieve the discomfort of MS. (C) 2012 Elsevier B.V. All rights reserved.
Spatial and temporal EEG dynamics of motion sickness
(2010-02-01)
Chen, Yu-Chieh
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Duann, Jeng-Ren
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Chuang, Shang-Wen
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Lin, Chun-Ling
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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.