Code-division multiplexed resistive pulse sensor networks for spatio-temporal detection of particles in microfluidic devices
  Spatial separation of suspended particles based on contrast in their physical
or chemical properties forms the basis of various biological assays performed
on lab-on-achip devices. To electronically acquire this information, we have
recently introduced a microfluidic sensing platform, called Microfluidic CODES,
which combines the resistive pulse sensing with the code division multiple
access in multiplexing a network of integrated electrical sensors. In this
paper, we enhance the multiplexing capacity of the Microfluidic CODES by
employing sensors that generate non-orthogonal code waveforms and a new
decoding algorithm that combines machine learning techniques with minimum
mean-squared error estimation. As a proof of principle, we fabricated a
microfluidic device with a network of 10 code-multiplexed sensors and
characterized it using cells suspended in phosphate buffer saline solution.
