Advancements in Microfluidic Technologies for Male Infertility

Abstract

Infertility affects ≈15% of couples worldwide, with ≈45% of these cases involving male factors. Semen analysis and sperm selection are critical and routine steps in achieving successful assisted reproductive outcomes. Conventional methods, which are widely used in clinics, are manual, subjective, time-consuming, and simply not sufficient for the highly complex and multifaceted task of sperm analysis. Recently, microfluidics-based devices, combined with high-resolution microscopy, have offered promising opportunities for evaluating sperm quality, gaining a fundamental understanding of sperm motion, and selection of high-quality sperm. Machine learning (ML) has also introduced automation and standardization in analyzing sperm morphology, intracellular characteristics, and motility. In this review, these state-of-the-art methods are comprehensively discussed and provide directions to address unresolved challenges.