用于从干扰物中实时鉴别多巴胺的主成分回归（PCR）的现场可编程门阵列（FPGA）实现。
FPGA implementation of principal component regression (PCR) for real-time differentiation of dopamine from interferents.
作者信息
Bozorgzadeh Bardia, Covey Daniel P, Garris Paul A, Mohseni Pedram
出版信息
Annu Int Conf IEEE Eng Med Biol Soc. 2015;2015:5151-4. doi: 10.1109/EMBC.2015.7319551.
This paper reports on field-programmable gate array (FPGA) implementation of a digital signal processing (DSP) unit for real-time processing of neurochemical data obtained by fast-scan cyclic voltammetry (FSCV) at a carbonfiber microelectrode (CFM). The DSP unit comprises a decimation filter and two embedded processors to process the FSCV data obtained by an oversampling recording front-end and differentiate the target analyte from interferents in real time with a chemometrics algorithm using principal component regression (PCR). Interfaced with an integrated, FSCV-sensing front-end, the DSP unit successfully resolves the dopamine response from that of pH change and background-current drift, two common dopamine interferents, in flow injection analysis involving bolus injection of mixed solutions, as well as in biological tests involving electrically evoked, transient dopamine release in the forebrain of an anesthetized rat.
本文报道了一种现场可编程门阵列（FPGA）实现的数字信号处理（DSP）单元，用于对通过碳纤维微电极（CFM）上的快速扫描循环伏安法（FSCV）获得的神经化学数据进行实时处理。该DSP单元包括一个抽取滤波器和两个嵌入式处理器，用于处理由过采样记录前端获得的FSCV数据，并使用主成分回归（PCR）化学计量学算法实时区分目标分析物和干扰物。该DSP单元与集成的FSCV传感前端相连，在涉及混合溶液大剂量注射的流动注射分析以及涉及麻醉大鼠前脑电诱发瞬态多巴胺释放的生物测试中，成功地从pH变化和背景电流漂移（两种常见的多巴胺干扰物）的响应中分辨出多巴胺响应。
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