ArticleIEEE sensors journal2018
Node-Pore Coded Coincidence Correction: Coulter Counters, Code Design, and Sparse Deconvolution.
Article in IEEE sensors journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Code-multiplexed multi-frequency impedance cytometry with a unified deep-unfolding network.Microsystems & nanoengineering · 2026Article
- Multi-Zone Visco-Node-Pore Sensing: A Microfluidic Platform for Multi-Frequency Viscoelastic Phenotyping of Single Cells.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Metal-pad-enhanced resistive pulse sensor reveals complex-valued Braess paradox.Physical review. E · 2023Article
- Single-cell microfluidic impedance cytometry: from raw signals to cell phenotypes using data analytics.Lab on a chip · 2021Article
- Node-Pore Sensing for Characterizing Cells and Extracellular Vesicles.Methods in molecular biology (Clifton, N.J.)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
We present a novel method to perform individual particle (e.g. cells or viruses) coincidence correction through joint channel design and algorithmic methods. Inspired by multiple-user communication theory, we modulate the channel response, with Node-Pore Sensing, to give each particle a binary Barker code signature. When processed with our modified successive interference cancellation method, this signature enables both the separation of coincidence particles and a high sensitivity to small particles. We identify several sources of modeling error and mitigate most effects using a data-driven self-calibration step and robust regression. Additionally, we provide simulation analysis to highlight our robustness, as well as our limitations, to these sources of stochastic system model error. Finally, we conduct experimental validation of our techniques using several encoded devices to screen a heterogeneous sample of several size particles.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.