Model-Based Robotic Cell Aspiration: Tackling Nonlinear Dynamics and Varying Cell Sizes

Abstract

Aspirating a single cell from the outside to the inside of a micropipette is widely used for cell transfer and manipulation. Due to the small volume of a single cell (picoliter) and nonlinear dynamics involved in the aspiration process, it is challenging to accurately and quickly position a cell to the target position inside a micropipette. This letter reports the first mathematical model that describes the nonlinear dynamics of cell motion inside a micropipette, which takes into account oil compressibility and connecting tube's deformation. Based on the model, an adaptive controller was designed to effectively compensate for the cell position error by estimating the time-varying cell medium length and speed in real time. In experiments, small-sized cells (human sperm, head width: ~3 μm), medium-sized cells (T24 cancer cells, diameter: ~15 μm), and large-sized cells (mouse embryos, diameter: ~90 μm) were aspirated using different-sized micropipettes for evaluating the performance of the model and the controller. Based on aspirating 150 cells, the model-based adaptive control method was able to complete the positioning of a cell inside a micropipette within 6 seconds with a positioning accuracy of ±3 pixels and a success rate higher than 94%.