Journal
2019 6TH IEEE PORTUGUESE MEETING IN BIOENGINEERING (ENBENG)
Volume -, Issue -, Pages -Publisher
IEEE
DOI: 10.1109/enbeng.2019.8692507
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Funding
- Fundacao para a Ciencia e a Tecnologia, through the doctoral program AIM - Applied Integrated Microsystems [PD/BD/128205/2016, PD/BD/128208/2016]
- Fundação para a Ciência e a Tecnologia [PD/BD/128205/2016, PD/BD/128208/2016] Funding Source: FCT
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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.
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