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In this paper, a highly-integrated multiprocessor chip design enabling the real-time processing of biomedical signals in portable brain-heart monitoring systems is presented. The architecture comprises a novel diffuse optical tomography (DOT) processor for taking brain imaging, an independent component analysis (ICA) processor for removing artifacts of brain electroencephalogram (EEG) signals, and...
This paper presents a low-power VLSI implementation of a 4-channel independent component analysis (ICA) processor for portable EEG signal processing applications. The low-power scheme employed for this ICA chip is based on power gating and clock gating by utilizing Cadence common power flow (CPF) low-power methodology and also according to the characteristics of ICA training behavior using different...
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...
This paper presents a complexity-efficient architecture for an EEG signal separation processor incorporating ICA with lossless data compression. An average correlation result of 0.9044 is achieved while transmitted EEG data bandwidth and power consumption are reduced by 41.6%. The chip area, operating frequency, and estimated power consumption of the proposed EEG architecture in UMC 90nm SP-HVT CMOS...
In this paper, an overview of a brain-heart monitoring system is first given. The latest development in miniature brain-heart monitoring system for emerging health applications is highlighted. Finally, the development of a low power biomedical signal processing and image reconstruction SoC design is presented. The significance of this SoC is to enable practical developments of portable real-time brain-heart...
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