Digital signal processing methods for impedance microfluidic cytometry
Digital signal processing methods for impedance microfluidic cytometry
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DOI：
10.1007/s10404-008-0315-3
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发表时间：
2009-02-01
影响因子：
2.8
通讯作者：
Morgan, Hywel
中科院分区：
文献类型：
--
作者：
Sun, Tao;van Berkel, Cees;Morgan, Hywel
阻抗微流控细胞术是一种非侵入性、无标记的技术，可以高速表征单个颗粒（珠子/细胞）的介电特性。在本文中，我们展示了如何将数字信号处理方法应用于阻抗信号的噪声去除和信号恢复的阻抗微流控细胞术。使用了两种方法;相关性来识别来自颗粒的典型信号，对于噪音较大的环境，使用自适应滤波器来去除噪音。从相关系数和信噪比两个方面定量地说明了自适应滤波的优点。最后，将自适应滤波方法与Savitzky-Golay滤波方法进行了比较。
Impedance microfluidic cytometry is a non-invasive, label-free technology that can characterize the dielectric properties of single particles (beads/cells) at high speed. In this paper we show how digital signal processing methods are applied to the impedance signals for noise removal and signal recovery in an impedance microfluidic cytometry. Two methods are used; correlation to identify typical signals from a particle and for a noisier environment, an adaptive filter is used to remove noise. The benefits of adaptive filtering are demonstrated quantitatively from the correlation coefficient and signal-to-noise ratio. Finally, the adaptive filtering method is compared to the Savitzky-Golay filtering method.