Analytical Strategy for Magnetic Flow Cytometry Signals Classification

Magnetic flow cytometers are promising tools to address cell detection and counting in a seamless and compact manner. Such devices integrate magnetic sensors with microfluidics for sample transportation and magnetic particles as reporters. This work presents a signal analysis method developed to address one of the challenges in magnetic flow cytometry: the ability to distinguish signatures of free or clustered magnetic particles from magnetically labelled targets. Comparing the sensor output signals (pulse amplitude vs. pulse width analysis) with simulations we develop a reliable classification methodology for labelled targets based on a custom Matlab algorithm. Upon discrimination of different signatures for clusters or single particles, one can reduce the number of false positives while improving the detection system accuracy.