Abstract
IntroductionSemen analysis is a clinical method aimed at determining the fertility of a male individual. The traditional subjective method lacks the reliability that can be achieved by computer-assisted sperm analysis (CASA) technology. Unfortunately, this technology has only been used when taking into consideration individually different sperm characteristics. The aim of this work is to present an integrative mathematical approach that considers different seminal variables to establish human sperm subpopulations. MethodsSamples were obtained from thirteen volunteers via masturbation and were analyzed by the routine subjective method and two objective systems, CASA Motility (CASA-Mot) and CASA Morphology (CASA-Morph). ResultsSeminogram variables were reduced to three principal components (PC) showing two subpopulations. Kinematics and morphometric variables each rendered three PCs for four subpopulations. ConclusionsThese results lay the foundations for future studies including different geographical, social, ethnic and age range conditions with the aim of achieving a definitive view of the human semen picture.
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