Frequency-Time Domain (FTD) Impedance Data Analysis to Improve Accuracy of Microparticle Enumeration in a Microfluidic Electronic Counter.

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.