A GMR-based magnetic flow cytometer using matched filtering

Abstract

In this work, signal processing techniques such as matched filtering and cross-correlation were applied to improve the detection efficiency in magnetic flow cytometry measurements with a SNR as low as 4.5 dB, a 3-fold improvement over thresholding alone. A multi-stripe GMR sensor was fabricated to improve the discrimination between magnetic nanoparticles (MNPs) and interference/noise such as motion artifacts. Time-of-flight between successive sensors in the array enables multiparametric and hydrodynamic analysis of cells. Detection of 4.5 pm MNPs and polymer microbeads decorated with MNPs, serving as a biomimetic model of cells, shows proof-of-principle. This setup was then optimized for future cell detection experiments.