Sergounioti, A.; Alonaris, E.; Rigas, D.

Background: Accurate characterization of human sperm motility is crucial for understanding male fertility potential. Traditional motility assessment methods primarily focus on static velocity parameters, often overlooking temporal declines in motility during the sperm trajectory. Objective: We aimed to develop and validate a novel fatigue-based profiling approach to assess intra-trajectory motility decline in human spermatozoa. Methods: Using computer-assisted sperm analysis (CASA)-derived motion tracking data, we introduced the Fatigue Index, a metric quantifying the decline in forward progression over time. We performed descriptive and inferential analyses to examine motility patterns, complemented by multivariate dimensionality reduction and clustering techniques. Results: Our analysis revealed significant intra-trajectory fatigue effects that traditional static parameters failed to capture. Fatigue-based profiling distinguished hidden subpopulations of sperm trajectories with distinct motility dynamics. The proposed Fatigue Index demonstrated robust consistency across samples and correlated with key kinematic features. Conclusions: Fatigue-based temporal profiling offers a new dimension for understanding sperm motility, highlighting the dynamic nature of forward progression and identifying subtle motility impairments that may be overlooked by conventional assessment methods.