Browsing by Author "Fu, Chih-Chung"

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A Hardware Design for Portable Continuous Wave Diffuse Optical Tomography
(2010)
Kang, Shih
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Wu, Shih-Yang
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Fu, Chih-Chung
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Chua, Ericson
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Hsu, Yuan-Huang
In recent years, the rapid development of diffuse optical tomography (DOT) technology has made possible many successful applications in the field of biomedicine, such as breast cancer detection and observation of oxygenated hemoglobin distribution in the brain. In this work, we build an inexpensive and portable real-time continuous wave near-infrared (CW-NIR) DOT system hardware suitable for use in system on a chip (SOC) applications. With greatly reduced system volume, the system can pave the way for practical developments in the clinical setting. The proposed system processes digitized biomedical signals acquired from a front-end sensor circuit, and can operate in either continuous or discontinuous mode according to user settings. Finally, we demonstrate the improvements in image reconstruction associated with the two-dimensional (2D) post-processing technique employed in the proposed system.
A Hardware-Efficient VLSI Implementation of a 4-Channel ICA Processor for Biomedical Signal Measurement
(2011)
Chen, Chiu-Kuo
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Chua, Ericson
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Fu, Chih-Chung
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Tseng, Shao-Yen
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Fang, Wai-Chi
This paper presents a 4-channel ICA implementation in the separation of EEG signals for on-line monitoring and analysis of brain functionalities. A novel ICA architecture utilizing mixed sequential, pipelined, and parallel processing units and employing interleaved and circular-based RAM modules to achieve hardware-efficient design is presented. The ICA processor is fabricated using UMC 90nm High-Vt CMOS technology.
A VLSI-inspired Image Reconstruction Algorithm for Continuous-wave Diffuse Optical Tomography Systems
(2009)
Hsu, Yuan-Huang
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Fu, Chih-Chung
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Fang, Wai-Chi
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Sang, Tzu-Hsien
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電子工程學系及電子研究所
In recent years, there has been an increasing interest in diffuse optical tomography (DOT). The image accuracy and computational complexity are greatly affected by the reconstruction algorithm. This paper aims at providing an efficient reconstruction technique which can be implemented in VLSI for advanced portable devices. Various inhomogeneous absorption models are used in simulations of continuous-wave DOT systems. The accuracy and time consumption are calculated and compared for both frame and sub-frame modes. Mean square errors (MSE) are derived to quantify the accuracy of different modes. Decreasing the complexity of algorithm and enhancing the quality of image can be achieved by adjusting the truncated parameter and reconstructive mode. This study has shown that the sub-frame mode with truncated Jacobi Singular Value Decomposition (TJSVD) algorithm is the method with higher efficiency and better quality. It can also be implemented in VLSI for continuous-wave DOT.
Portable Brain-Heart Monitoring System
(2010)
Fu, Chih-Chung
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Chen, Chiu-Kuo
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Tseng, Shao-Yen
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Kang, Shih
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Chua, Ericson
A portable brain-heart monitoring system is proposed to integrate and miniaturize those heavy equipments in the hospitals. The system comprises a 4-channel independent component analysis (ICA) engine for artifact removal from EEG, a heart-rate variability (HRV) analysis engine for on-line HRV analysis and a diffuse optical tomography (DOT) engine for reconstruction of the absorption coefficient image of the brain tissue. A lossless compression module achieves 2.5 compression ratio is also employed to reduce the power consumption of the wireless transmission. EEG, EKG and near-infrared signals acquired from the analog front-end IC are processed in real-time or bypassed according to user configurations. Processed data and raw data are compressed and sent to a remote science station by a commercial Bluetooth module for further analysis and 3-D visualization and remote diagnosis. The ICA and HRV engine are verified by real EEG and EKG signals while the DOT engine is verified by an experimental model. The system is implemented using UMC 65nm CMOS technology, and the core size is 680x680 um(2), and the estimated power consumption of the chip working at 24 MHz under full mode is 3.6 mW.
VLSI Implementation of a Mixed Bio-signal Lossless Data Compressor for Portable Brain-Heart Monitoring Systems
(2011)
Chua, Ericson
;
Fu, Chih-Chung
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Fang, Wai-Chi
;
電子工程學系及電子研究所
;
Department of Electronics Engineering and Institute of Electronics
This paper presents a highly integrated VLSI implementation of a mixed bio-signal lossless data compressor capable of handling multichannel electroencephalogram (EEG), electrocardiogram (ECG) and diffuse optical tomography (DOT) bio-signal data for reduced storage and communication bandwidth requirements in portable, wireless brain-heart monitoring systems for use in the hospital or home care setting.