Mechanical Force Estimation Based on Visual Cell Deformation and Improved Point-Load Model

Abstract

Measuring the mechanical force applied to a cell during penetration has long been studied. However, existing sensor methods can disturb or even prevent a planned cell surgery because of their physical units. We propose a contactless mechanical force estimation method based on an improved point-load model and cell contour detection. We extended the point-load model to large cell deformations and obtained a relationship between the mechanical force and the morphology of the deformed cell. We designed two cell contour detection methods for visually detecting the deformation of different cell morphologies to obtain the geometric parameters required by the model. Finally, we carried out penetration experiments on porcine oocytes and zebrafish embryos. The contour detection methods showed a consistency of up to 99.29% compared with manual marking, and the force estimation accuracy was 1.05 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{N}$ </tex-math></inline-formula> . We compared the estimation results of our method with measurements taken in real experiments and confirmed that our method accurately estimated the mechanical force applied to the cell without contact. Thus, it may be applied to estimating the applied force during cell surgery in real time.