In this article, we introduce the real-time cellular force microscope (RT-CFM), a high-throughput microrobotic platform for mechanical stimulation and characterization of single cells. We developed computer vision algorithms that fully automate the positioning of target cells and localization of the sensor tip. The control and acquisition architecture dramatically increases the accuracy, speed, and reliability of force measurements. Pollen tubes provide an ideal model system for the study of plant mechanics at the single-cell level. To quantitatively obtain the physical properties of the plant cell wall, we generated topography and stiffness measurements from 3D scans of living, growing pollen tubes. We report techniques for real-time monitoring and analysis of intracellular calcium fluxes during mechanical intervention. Our platform is compatible with various imaging systems and enables a powerful screening technology to facilitate biomechanical and morphological characterization of developing cells.

We present a microrobotic platform that combines MEMS-based capacitive force sensing technology, a dual-stage positioning system and a real-time control and acquisition architecture with computer vision automation to manipulate and mechanically characterize growing plant cells. The topography accuracy of the system, using a silicon wafer sample is measured to be 28 nm (1σ, 200Hz). With an SI-traceable stiffness reference we estimate the accuracy of the RT-CFM to be 3.49%. The target locations are selected from an interactive image of the workspace, and the sensing tip is positioned at each location using visual servoing techniques. Topography and stiffness maps were successfully obtained on growing pollen tubes. With the proposed system, cells can be mechanically stimulated at high speeds and with high precision while the intracellular components are visualized using confocal imaging. The system offers a versatile solution for dexterous and highthroughput characterization of biological specimen.