Morphological analysis of metabolically dysregulated spermatozoa using Artificial Intelligence based approach

sperm motility analysis



spermatozoa, Sperm Motility, Sperm movement, Sperm morphology, CASA, Male Infertility, Artificial Intelligence, Convolutional Neural Network, CNN, Sexual Health


Sperm motility is an important parameter in evaluation of infertility in human semen samples and it’s directly associated with the Asthenozoospermia. Poor sperm movements are often related to less production of adenosine triphosphate (ATP), or due to less lactate fermentation and oxidative phosphorylation in mitochondria. In this article, Computer Assisted Sperm Analysis (CASA) based on Convolutional Neural Network (CNN) an Artificial Intelligence (AI) approach have been reported for the understanding of flagellar waveforms and propagation of sperm movement. We also show how microscopy systems are used for evaluating spermatozoa movements and to find the difference in their movement pattern, path length and area followed by flagella of sperm and how it links to its metabolic regulation. We found that sperms covering a distance less than 40µm/sec are metabolically dysregulated or are considered to produce less amount of ATP which could be a possible reason for no fertilization of ova in women. It also suggests that the flagella of sperm are linked with the metabolic activity of the sperm and its movement which affects the rate of the fertilization.


Author Biographies

Nihar Ranjan Bhoi, Indira Fertility Academy, Udaipur

Indira IVF Hospital,
Indira Fertility Academy,
Udaipur, Rajasthan -313001, India

Neel Mani, Dev Sanskriti Vishwavidyalaya, Haridwar

Centre of Artificial Intelligence and Research (CAIR),
Dev Sanskriti Vishwavidyalaya,
Haridwar, Uttarakhand -249411, India

Brijesh Rathi, University of Delhi

Laboratory for Translational Chemistry and Drug Discovery,
Department of Chemistry, Hansraj College,
University of Delhi, Delhi -110 007, India

Dhruv Kumar, UPES University, Dehradun

School of Health Sciences & Technology,
UPES University, Dehradun,
Uttarakhand - 248007




How to Cite

Maurya, S., Raj, S., Bhoi, N. R., Mani, N., Rathi, B., & Kumar, D. (2023). Morphological analysis of metabolically dysregulated spermatozoa using Artificial Intelligence based approach. Journal of Integrated Science and Technology, 11(4), 569. Retrieved from



Biomedical and Pharmaceutical Sciences