An AI-Guided Mechanotyping Instrument for Fully Automated Oocyte Quality Assessment.

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 low automation levels and predominantly provide local, rather than whole-cell, mechanical characterization. To address these limitations, we developed an AI-guided µN-scale mechanical measurement instrument for safe and automated oocyte quality assessment. The instrument 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 instrument captures cellular deformation in real time, enabling precise calculation of the oocyte's compressive modulus. This measurement instrument 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).