An AI-guided mechanotyping instrument for fully automated oocyte quality assessment

TL;DR

This paper introduces an AI-guided, automated, and non-destructive system for measuring oocyte mechanical properties, improving accuracy and safety in assessing oocyte quality for IVF and ART.

Contribution

The authors developed a novel AI-integrated micromechanical system that automates oocyte assessment, reducing damage and measurement errors compared to existing methods.

Findings

Enables real-time, precise measurement of oocyte compressive modulus.

Automates oocyte quality screening with high accuracy.

Reduces cellular damage during mechanical assessment.

Abstract

The mechanical properties of oocytes are regarded as important indicators of their developmental potential. During fertilization, deviations from the normal mechanical range can hinder sperm penetration, ultimately reducing fertilization efficiency and compromising embryo quality. However, current methods for measuring oocyte mechanics often suffer from serious cellular damage, low automation levels, and large measurement errors. To address these limitations, we developed an AI-guided micronewton-scale mechanical measurement system for safe and automated oocyte quality assessment. The system integrates voice interaction with automated experimental workflows to control a magnetically actuated microgripper, which applies defined loading forces to induce micron-scale compressive deformation of the oocyte. Combined with AI-assisted object detection and image segmentation algorithms, the system captures cellular deformation in real time, enabling precise calculation of the oocyte's compressive modulus. This measurement system enables automated, quantitative, and non-destructive evaluation of oocyte mechanical properties, providing an effective approach for oocyte quality screening in in vitro fertilization (IVF) and other assisted reproductive technologies (ART).