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

Abstract

Microfluidic impedance cytometry is a powerful system to measure micro and nano-sized particles and is routinely used in point-of-care 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 × 100 µm wide (with 30 µm wide focused aperture) microchannel and gold coplanar microelectrodes that generate 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 data set, we also performed a compendium of characterization experiments including variations in flow rate, input voltage, and particle size. Multivariate 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 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.

Particle Counting Methods Based on Microfluidic Devices

“…Various approaches have been explored to improve sensitivity, including the use of focused flow and new structural systems and techniques [ 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 ]. A popular approach to focusing stream has been the use of non-conducting solutions such as pure water.…”

“…They also counted particles by local DC dielectric electrophoretic forces, successfully separating and counting two and three different sizes of polystyrene particles with 1 mm resolution. Zhang et al [ 80 ] proposed a novel device with five identical sensing regions connected in series and multiple cross-correlation analysis that enhances the sizing SNR by a factor of n 1/2 , where n is the pore numbers in series, as shown in Figure 6 c. Additionally, a novel signal averaging algorithm has also been developed by Ashley et al [ 83 , 84 ] that reduces noise in microfluidic impedance cell counting data, improves enumeration accuracy, and reduces detection limits. These innovative technologies have significantly improved the sensitivity and accuracy of particle detection and counting in microfluidic systems.…”

Antibody-functionalized aluminum oxide-coated particles targeting neutrophil receptors in a multifrequency microfluidic impedance cytometer

“…Protocols for microfabricating coplanar electrodes and PDMS microchannels have been described in previous articles. 18 Briefly, 250 nm of chromium followed by 750 nm of gold was sputtered above glass wafers exposed to UV light with electrode dimensions using photolithography, forming the gold electrodes (Fig. 1c).…”

“…Among different sensing modalities, impedance cytometry stands out as a revolutionary tool to directly or indirectly detect the presence of both microscopic and/or nanoscopic objects, obtaining electrical information of such species without sample destruction at high-throughputs. 13,14 It has many useful applications, from size referencing in particle fabrication, [15][16][17][18] air and water quality reporting, [19][20][21][22][23] and most notoriously in biological cell assessments and disease diagnostics. [24][25][26][27] While accurate, its main advantage may come from manufacturing scalability, an attractive feature for point-of-care environments.…”

Optimizing Microfluidic Impedance Cytometry by Bypass Electrode Layout Design

“…It is crucial to achieve sensitive and accurate cell detection results in MIC [9]. Various optimization techniques have been developed to enhance the performance of MIC platforms for bio-particle event detection, including improving the electrode layout [10][11][12][13], channel design [14][15][16][17], and data processing algorithms [18,19]. These optimizations aim to reduce the baseline noise, decrease the coefficient of variation (CV) of events, increase the signal-tonoise ratio (SNR) of particle events, and improve the detection capability of the MIC system.…”