Sex Estimation Using Bare Footprint Dimensions: A Review of Literature

Abstract

In forensic podiatry, bare footprints are considered an essential evidence element. The anthropometric and morphological study of the footprints takes into account both quantitative and qualitative features. Predictions of sexual dimorphism from bare footprints are deemed effective, pertaining to the fact that the overall body structure of humans influences the actual foot size. In the current review, 11 research articles have been identified that have exclusively focused on sex estimation from bare footprint dimensions across diverse demographic groups worldwide. The study found analytical techniques such as sectioning points, regression analysis, discriminant function analysis, and machine learning models have been used for sex estimation. The studies under review infer that different populations and best predictors have varying degrees of accuracy when compared to predicting sex from footprints. By pointing out that machine learning approaches are more accurate than traditional analytical methods, the study promotes their use in sex estimation from footprint dimensions for improving accuracy and analyzing large and complex datasets.

Keywords

Forensic podiatry / Footprint dimensions / Sex estimation / Anthropometry / Review of literature

Author Contributions

S.S. (Saumya Seal): Conceptualization, Literature search, Draft preparation, Review and editing, Final approval; S.S. (Suryakant Soni): Draft preparation, Review and editing, Final approval.

Ethics Statement

Not applicable.

Informed Consent Statement

Not applicable.

Funding

This research received no external funding.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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