The extracellular and interstitial fluids that surround cells have the potential to significantly impact the precision of single-cell impedance measurements in microfluidic applications. This study presents a mathematical method to compute cellular parameters directly, which is designed to function efficiently in environments characterized by low computational power and minimal energy consumption, and it is founded on the analytical solutions derived from the circuit model of the cell, which is both novel and unique. This system can operate utilizing only an 8-bit microcontroller to autonomously calculate the electrochemical parameters of cellular biology, thereby obviating the necessity for human intervention, numerical software, or machine learning preprocessing. The accuracy of this approach has been validated through theoretical and experimental studies involving multi-electrode impedance monitoring for B16-F10 melanoma cancer cells over 24 hours. The technique achieves an accuracy of up to 97% in impedance assessments of cells. This methodology allows for the arrangement of microelectrodes in any coplanar configuration in microfluidics, with the overall system impedance represented as the cumulative response from each electrode pattern, following the principles of superposition and homogeneity, thereby enabling the direct derivation of cytoplasmic and membrane parameters in the traditional electrochemical measurement framework. This modeling method is particularly advantageous for small-scale devices with limited computational resources, allowing widespread deployment. Furthermore, it could facilitate the rapid identification of variations in cellular parameters between cancerous cells, aiding in the diagnosis of melanoma and cancer metastasis.
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Sung‐Lin Tsai (2025) studied this question.
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