A nonlinear signal-specific ADC for efficient neural recording
作者： Mohsen Judy , M. Sodagar Amir , Reza Lotfi
DOI: 10.1109/BIOCAS.2010.5709560
关键词: Background noise 、 Quantization (signal processing) 、 Nonlinear system 、 Successive approximation ADC 、 Read-only memory 、 Electronic engineering 、 Analog-to-digital converter 、 Digitization 、 Noise measurement 、 Computer science
摘要: A bandwidth-efficient technique for nonlinearly converting analog neural signals into digital is presented to be used in implantable recording microsystems. It shown that the choice of a proper nonlinear quantization function helps reduce outgoing bit rate carrying recorded data. Another major benefit digitizing using analog-to-digital converter (ADC) improvement signal-to-noise ratio (SNR) signal. The 8-b anti-logarithmic ADC reported this paper digitizes large action potentials with 10b resolution, while quantizing small background noise resolution as low 3b. circuit was designed and simulated 0.18-um CMOS process. According experimental results, SNR signal increases from 5.11 before digitization 22 after being digitized proposed approach.
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