Time-domain signal averaging to improve microparticles detection and enumeration accuracy in a microfluidic impedance cytometer

Microfluidic impedance cytometry is a powerful system to measure micro and nano-sized particles and is routinely used in point-of-care settings disease diagnostics and other biomedical applications. However, small objects near a sensor’s detection limit are plagued with relatively significant background noise and are difficult to identify for every case. While many data processing techniques can be utilized to reduce noise and improve signal quality, frequently they are still inadequate to push sensor detection limits. Here, we report the first demonstration of a novel signal averaging algorithm effective in noise reduction of microfluidic impedance cytometry data, improving enumeration accuracy and reducing detection limits. Our device uses a 22 μm tall microchannel and gold coplanar microelectrodes that generates an electric field, recording bipolar pulses from polystyrene microparticles flowing through the channel. In addition to outlining a modified moving signal averaging technique theoretically and with a model dataset, we also performed a compendium of characterization experiments including variations in flow rate, input voltage, and particle size. Multi-variate metrics from each experiment are compared including signal amplitude, pulse width, background noise, and signal-to-noise ratio (SNR). Incorporating our technique resulted in improved SNR and counting accuracy across all experiments conducted, and the limit of detection improved from 5 μm to 1 μm particles without modifying microchannel dimensions. Succeeding this, we envision implementing our modified moving average technique to develop next generation microfluidic impedance cytometry devices with an expanded dynamic range and improved enumeration accuracy. This can be exceedingly useful for many biomedical applications, such as infectious disease diagnostics where devices may enumerate larger-scale immune cells alongside sub-micron bacterium in the same sample.

Impedance Characterization of Particles One by One Using a Nanosensor Electronic Platform

Impedance cytometry represents a technique that allows the electronic characterization of colloids and living cells in a highly miniaturized way. In contrast with impedance spectroscopy, the measurements are performed at a fixed frequency, providing real-time monitoring of the species traveling over the sensor. By measuring the electrical properties of particles in suspension, the dielectric characteristics (electric conductivity and capacitance) of both cells and particles can be readily determined. During the last years, this technique has been broadly investigated; however, it is still not trivial to differentiate particles of similar size based on their dielectric characteristics. A way to increase the discrimination abilities of this technique could be the integration of nanostructures into the impedance platforms. In this work, we present the impedance cytometry study of particles using microfluidic channels aligned over interdigitated gold nanowire structures as our impedimetric sensor. The characterization of particles of different sizes and their comparison with particles of different compositions will provide an understanding of the correlation between the electrical signal and the characteristics of each particle. This approach is an attractive element for label-free detection platforms that can be integrated into lab-on-a-chip systems and further implemented for single-cell analysis.