Frequency-Time Domain (FTD) Impedance Data Analysis to Improve Accuracy of Microparticle Enumeration in a Microfluidic Electronic Counter.
Frequency-Time Domain (FTD) Impedance Data Analysis to Improve Accuracy of Microparticle Enumeration in a Microfluidic Electronic Counter.
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DOI：
10.1109/embc46164.2021.9630635
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发表时间：
2021-11
期刊：
影响因子：
--
通讯作者：
Hassan U
中科院分区：
文献类型：
--
作者：
Ashley BK;Hassan U
生物传感器数据中存在的实验背景噪声阻碍了关键生物标志物的灵敏和准确检测的能力。在这里，我们报告了我们的数字信号处理分析与频域和时域（FTD）的数据，以减少在实验微流控阻抗细胞仪的噪声。我们独立地评估了所采用的噪声滤波技术的有效性，包括基线漂移校正、高频噪声滤波和电力线干扰缓解。我们进一步探索了所有滤波器的组合效果，并确定了信噪比（SNR）和颗粒计数精度的改进。通过消除噪声机制，SNR提高了这种阻抗细胞仪设备，我们未来的努力将探索更具体和不常见的噪声频谱的滤波效果，以更大程度地优化设备性能。
Experimental background noise present in biosensors’ data hinders the ability for sensitive and accurate detection of critical biomarkers. Here, we report our digital signal processing analysis with respect to frequency and time domain (FTD) data to reduce noise in an experimental microfluidic impedance cytometer. We evaluated the effectiveness of employed noise filtering techniques independently, including baseline drift correction, high frequency noise filtering, and powerline interference mitigation. We further explored the combined effect of all filters and determine improvements in signal-to-noise (SNR) ratio and particle counting accuracy. By removing noise regimes, SNR improved with this impedance cytometer device, and our future efforts will explore filtering effects of more specific and uncommon noise spectrums to greater optimize device performance.