Browsing by Author "Wang, Wan-Ru"

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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.
Low Complexity Real Time BCI for Stroke Rehabilitation
(2015)
Chou, Tsung-Pen
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Wang, Wan-Ru
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Chang, Tian Sheuan
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電子工程學系及電子研究所
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Department of Electronics Engineering and Institute of Electronics
Stroke rehabilitation with EEG-based brain computer interface enables interaction within injury neurons and restoration of original functions in motor area of brain. However, many approaches usually require high complexity for reliable detection and result in achieving real time computation difficultly. This study proposes a real time low complexity BCI interface for stroke rehabilitation, which is based on Filter-Bank Common Spatial Pattern (FBCSP) method. For reducing complexity purpose, EEG channels (electrodes) are reduced from 19 channels to 4 channels which are Fz, C3, Cz, and C4. Furthermore, the filter bank is reduced from five bands to three bands which are 4-7Hz, 8-12Hz, and 13-30Hz. We also develop a real time scheme by using one-second timing window for EEG analysis and adaptive algorithm to fit time-varying EEG. This approach not only reduces 87% computational complexity but also shows over 80% accuracy for offline analysis and 68% accuracy for online implementation within one-second response time.
Performance Optimized of the Novel Dry EEG Electrodes by using the Non-Dominated Sorting Genetic Algorithms (NSGA-II)
(2010)
Han, Ming-Feng
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Liao, Lun-De
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Liu, Yu-Hang
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Wang, Wan-Ru
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Lin, Bor-Shyh
In this study, a optimization process was performed for the developed dry electroencephalography (EEG) electrodes by using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to minima the skin-electrode impedance. The developed dry EEG electrodes can measure the EEG signals without any gels applied and no skin preparation. However, how to find a proper skin-electrode contact area is an important issue. The contact area is directly related to the electrodes impedance and fabrication cost. Therefore, the NSGA-II is used to searching the suitable contact area and other design parameters. NSGA-II is a wieldy used optimization method, especially for the multi-objectives issues like this case. Finally, we compare the results of the simulation and experiments for ensuring the optimal process. The experiment results show that using the optimal values provided from NSGA-II can achieve the minima skin-electrode impedance. It confirms the dry electrode can be effectively used for the cognitive or other applications in the future.