Browsing by Author "Chen, Po-Chuan"

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A Sliced Inverse Regression (SIR) Decoding the Forelimb Movement from Neuronal Spikes in the Rat Motor Cortex
(2016-12-09)
Yang, Shih-Hung
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Chen, You-Yin
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Lin, Sheng-Huang
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Liao, Lun-De
;
Lu, Henry Horng-Shing
Several neural decoding algorithms have successfully converted brain signals into commands to control a computer cursor and prosthetic devices. A majority of decoding methods, such as population vector algorithms (PVA), optimal linear estimators (OLE), and neural networks (NN), are effective in predicting movement kinematics, including movement direction, speed and trajectory but usually require a large number of neurons to achieve desirable performance. This study proposed a novel decoding algorithm even with signals obtained from a smaller numbers of neurons. We adopted sliced inverse regression (SIR) to predict forelimb movement from single-unit activities recorded in the rat primary motor (M1) cortex in a water-reward lever-pressing task. SIR performed weighted principal component analysis (RCA) to achieve effective dimension reduction for nonlinear regression. To demonstrate the decoding performance, SIR was compared to PVA, OLE, and NN. Furthermore, RCA and sequential feature selection (SFS) which are popular feature selection techniques were implemented for comparison of feature selection effectiveness. Among SIR, PVA, OLE, PCA, SFS, and NN decoding methods, the trajectories predicted by SIR (with a root mean square error, RMSE, of 8.47 +/- 1.32 mm) was closer to the actual trajectories compared with those predicted by PVA (30.41 +/- 11.73 mm), OLE (20.17 +/- 6.43 mm), PCA (19.13 +/- 0.75 mm), SFS (22.75 +/- 2.01 mm), and NN (16.75 +/- 2.02 mm). The superiority of SIR was most obvious when the sample size of neurons was small. We concluded that SIR sorted the input data to obtain the effective transform matrices for movement prediction, making it a robust decoding method for conditions with sparse neuronal information.
Cylindrical Liquid Crystal Lenses System for Autostereoscopic 2D/3D Display
(2012)
Chen, Chih-Wei
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Huang, Yi-Pai
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Chang, Yu-Cheng
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Wang, Po-Hao
;
Chen, Po-Chuan
The liquid crystal lenses system, which could be electrically controlled easily for autostereoscopic 2D/3D switchable display was proposed. The High-Resistance liquid crystal (HRLC) lens utilized less controlled electrodes and coated a high-resistance layer between the controlled-electrodes was proposed and was used in this paper. Compare with the traditional LC lens, the HR-LC Lens could provide smooth electric-potential distribution within the LC layer under driving status. Hence, the proposed HR-LC Lens had less circuit complexity, low driving voltage, and good optical performance also could be obtained. In addition, combining with the proposed driving method called dual-directional overdriving method, the above method could reduce the switching time by applying large voltage onto cell. Consequently, the total switching time could be further reduced to around 2second. It is believed that the LC lens system has high potential in the future.
Detecting Frontal EEG Activities with Forehead Electrodes
(2009)
Duann, Jeng-Ren
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Chen, Po-Chuan
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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.
Dual Direction Overdriving Method for Accelerating 2D/3D Switching Time of Liquid Crystal Lens on Auto-Stereoscopic Display
(2012-10-01)
Chen, Chih-Wei
;
Huang, Yi-Pai
;
Chen, Po-Chuan
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光電工程學系
;
Department of Photonics
In this paper, we investigate the dual direction overdriving method to accelerate both the 3D-on and 3D-off time of the lenticular liquid crystal (LC) lens. The experimental results indicated that the response time (tau(3D-on) and tau(3D-off)) was successfully improved for a factor of 4 as a thick (60 mu m cell gap) LC lens. The LC lens was also implemented on an auto-stereoscopic display to yield fast 2D/3D switching ability.