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Abstract
The ability to accurately quantify dielectrophoretic (DEP) force is critical in the development of high-efficiency microfluidic systems. This is the first reported work that combines a textile electrode-based DEP sensing system with deep learning in order to estimate the DEP forces invoked on microparticles. We demonstrate how our deep learning model can process micrographs of pearl chains of polystyrene (PS) microbeads to estimate the DEP forces experienced. Numerous images obtained from our experiments at varying input voltages were preprocessed and used to train three deep convolutional neural networks, namely AlexNet, MobileNetV2, and VGG19. The performances of all the models was tested for their validation accuracies. Models were also tested with adversarial images to evaluate performance in terms of classification accuracy and resilience as a result of noise, image blur, and contrast changes. The results indicated that our method is robust under unfavorable real-world settings, demonstrating that it can be used for the direct estimation of dielectrophoretic force in point-of-care settings.
Highlights
A nonuniform electrokinetic field is used to apply a force on uncharged or neutral particles resulting in the motion of the particle suspended in a medium by the interactions of this nonuniform electric field and the induced effective dipole moment of the particle [1–3]
Electric field-induced dipole formation causes pearl chaining of particles that are aligned along an electric field [4,5]
We show how deep learning can be used to precisely calculate the DEP force experienced by polystyrene beads in a polar medium
Summary
A nonuniform electrokinetic field is used to apply a force on uncharged or neutral particles resulting in the motion of the particle suspended in a medium by the interactions of this nonuniform electric field and the induced effective dipole moment of the particle [1–3]. Dielectrophoretic (DEP) forces assemble particles from aqueous suspensions into long electrically conductive nano/microstructures due to positioning, convection, and levitation. Electric field-induced dipole formation causes pearl chaining of particles that are aligned along an electric field [4,5]. Pearl chains are direct indicators of DEP forces and can be correlated to dielectric variations of a variety of microparticles, including biological cells [1–3,6,7]. Despite the fact that dielectrophoresis is becoming increasingly relevant in point-ofcare systems [6], DEP force estimation is still theoretical. The computation of the DEP force acting on a particle has been described as a challenging task unless numerous simplifying assumptions and relatively simple geometries are taken into account [4], and these are commonly based on Pohl’s dipole approximation [1]
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