Efficient management of foot disorders requires knowledge of plausible sexual dimorphic differences in the foot structure and function. Knowledge about foot dimorphism is yet unsettled. In the present study, we mapped the multizone plantar pressure distribution in a cohort of 298 healthy subjects of both sexes using the piezoelectric pedobarographic recordings. We investigated the hypothesis that sexual foot dimorphism would entail differences in plantar pressure distribution. We delved into the issue using the k-nearest neighbors' classifier (k-NN), a supervised machine learning algorithm, to predict the correct foot phenotype classification based on the plantar pressure and anthropometric and structural features. Based on the similarity measures, the classifier assigns unknown input data to the most common class, men or women, among the closest neighbors. The major finding was the unraveling of sex-specific foot dimorphism in healthy people. The k-NN was able to recognize the person's sex based on a few discriminatory features, with an outstandingly low misclassification rate. The pressure distribution on the plantar surface of the great toe, one of the orthopedic plantar surface zones, is the most distinct feature in differentiating the foot phenotype. The results also unraveled the presence of individuals whose foot features paradoxically corresponded with those classified for the opposite sex, i.e., the female foot was classified in the men's group and vice versa. In conclusion, the study supports the presence of sexual foot dimorphism. A pedobarographic examination supplemented with the k-NN algorithm for machine learning allows one to discriminate the foot sexual phenotype with high accuracy. The foot phenotype identities exist outside the gender binary. Insights into sexual foot dimorphism may streamline the management of foot disorders. Keywords Biomechanics " Foot " K-nearest neighbors' algorithm " Pedobarography " Plantar pressure " Foot dimorphism.

Center for Vision Speech and Signal Processing University of Surrey Guildford UK; Department of Management and Accounting SGH Warsaw School of Economics Warsaw Poland

Zobrazit více v PubMed

Kolesár DM, Kujal P, Mrázová I, Pokorný M, et al. Sex-linked differences in cardiac atrophy after mechanical unloading induced by heterotopic heart transplantation. Physiol Res. 2024;73:9–25. doi: 10.33549/physiolres.935217. PubMed DOI PMC

Kobayashi K, Sasase T, Maekawa T, et al. Immune disorders and sex differences in spontaneously diabetic Torii rats, type 2 diabetic model. Physiol Res. 2022;71:113–123. doi: 10.33549/physiolres.934825. PubMed DOI PMC

Matsumoto Y, Ogihara N, Kosuge S, Hanawa H, Kokubun T, Kanemura N. Sex differences in the kinematics and kinetics of the foot and plantar aponeurosis during drop-jump. Sci Rep. 2023;13:12957. doi: 10.1038/s41598-023-39682-6. PubMed DOI PMC

Ugbolue UC, Yates EL, Wearing SC, et al. Sex differences in heel pad stiffness during in vivo loading and unloading. J Anat. 2020;237:520–528. doi: 10.1111/joa.13207. PubMed DOI PMC

Talia AJ, Busuttil NA, Kendal AR, Brown R. Gender differences in foot and ankle sporting injuries: A systematic literature review. Foot (Edinb) 2024;60:102122. doi: 10.1016/j.foot.2024.102122. PubMed DOI

Lorkowski J, Gawronska K, Pokorski M. Pedobarography: a review on methods and practical use in foot disorders. Appl Sci. 2021;11:11020. doi: 10.3390/app112211020. DOI

Lorkowski J. Methodology of pedobarographic examination - own experiences and review of literature. Przegl Lek. 2006;63(Suppl 5):23–27. PubMed

Basheer I, Hajmeer MN. Artificial neural networks: fundamentals, computing, design, and application. J Microbiol Meth. 2001;43:3–31. doi: 10.1016/S0167-7012(00)00201-3. PubMed DOI

Carpenter GA, Grossberg S. Learning, categorization, rule formation, and prediction by fuzzy neural network. In: CHEN CH, editor. Fuzzy Logic and Neural Network Handbook. New York: McGraw-Hill; 1995.

Devijver PA, Kittler J. Pattern Recognition: A Statistical Approach. Prentice/Hall International; 1982.

Olejarczyk E, Jozwik A, Valiulis V, Dapsys K, Gerulskis G, Germanavicius A. Statistical analysis of graph-theoretic indices to study EEG-TMS connectivity in patients with depression. Front Neuroinform. 2021;15:651082. doi: 10.3389/fninf.2021.651082. PubMed DOI PMC

Larsen CS. Equality for the sexes in human evolution? Early hominid sexual dimorphism and implications for mating systems and social behavior. Proc Natl Acad Sci USA. 2003;100:9103–9104. doi: 10.1073/pnas.1633678100. PubMed DOI PMC

Ogden CL, Fryar CD, Carroll MD, Flegal KM. Vital and Health Statistics; no 347 (Mean body weight, height, and body mass index, United States 1960–2002) 2004. [Accessed on 5 June 2025]. https://www.cdc.gov/nchs/data/ad/ad347.pdf . PubMed

Wolchover N. LiveScience (Men vs. women: our key physical differences explained) 2011. [Accessed 5 June 2025]. https://www.livescience.com/33513-men-vs-women-our-physical-differences-explained.html .

Adelakun SA, Ogunlade B, Akingbade GT, Olayemi OT, Fidelis OP, Owolabi FM. Sexual dimorphism and anthropometric measurements of foot in adult Oyemekun ethnic group population in Akure, South-West Nigeria. J Biol Med. 2019;3:027–030. doi: 10.17352/jbm.000009. DOI

Suleiman MO, Danborno B, Musa SA, Timbuak JA. Sexual dimorphism and determination using foot outlines, footprint angles, and foot indices. Forensic Sci Med Pathol. 2024;20:614–626. doi: 10.1007/s12024-023-00711-5. PubMed DOI

Krishan K, Kanchan T, Passi N, DiMaggio JA. Sexual dimorphism in foot length ratios among North Indian adolescents. J Forensic Leg Med. 2015;36:96–101. doi: 10.1016/j.jflm.2015.09.007. PubMed DOI

Williams BT, Hunt KJ. Hallux Rigidus: anatomy and pathology. Foot Ankle Clin. 2024;29:371–387. doi: 10.1016/j.fcl.2023.12.002. PubMed DOI

Cai Y, Song Y, He M, He W, Zhong X, Wen H, Wei Q. Global prevalence and incidence of hallux valgus: a systematic review and meta-analysis. J Foot Ankle Res. 2023;16:63. doi: 10.1186/s13047-023-00661-9. PubMed DOI PMC