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• W4367359552 abstract "There is an increasing demand for real-time neural signal monitoring from a large number of electrodes to provide adequate spatial and temporal resolution for high-density brain neural interfaces. This paper proposes an adaptive multi-channel neural recording system that can record neural signals from a large number of electrodes using a smaller number of recording channels. The system utilizes an adaptive electrode selection technique to automatically scan the electrodes where neural spikes occur and record those selected electrodes. A proposed 32-electrode neural recording prototype, including 12 recording channels and 8 scanning channels, was fabricated in a 180-nm CMOS process and tested <italic xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>in vitro</i> . With pre-recorded neural data, the system verified that the occurrence of neural spikes in specific electrodes could be detected and processed in real-time, enabling automatic electrode selection. Measured results showed that the proposed system could lead to over 40% reduction in silicon area compared to conventional works." @default.
• W4367359552 created "2023-04-30" @default.
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• W4367359552 date "2023-07-01" @default.
• W4367359552 modified "2023-10-16" @default.
• W4367359552 title "A Multi-Channel Neural Recording System With Neural Spike Scan and Adaptive Electrode Selection for High-Density Neural Interface" @default.
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• W4367359552 doi "https://doi.org/10.1109/tcsi.2023.3268686" @default.
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