Sex and stature estimation from anthropometric measurements of the foot: linear analyses and neural network approach on a Turkish sample

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dc.authoridParlak, Muhammed Emin/0000-0002-6614-9903
dc.contributor.authorParlak, Muhammed Emin
dc.contributor.authorOezkul, Bengue Berrak
dc.contributor.authorOruc, Mucahit
dc.contributor.authorCelbis, Osman
dc.date.accessioned2024-08-04T20:55:56Z
dc.date.available2024-08-04T20:55:56Z
dc.date.issued2024
dc.departmentİnönü Üniversitesien_US
dc.description.abstractBackground For over a century, anthropometric techniques, widely used by anthropologists and adopted by medical scientists, have been utilized for predicting stature and sex. This study, conducted on a Eastern Turkish sample, aims to predict sex and stature using foot measurements through linear methods and Artificial Neural Networks. Our research was conducted on 134 medical students, comprising 69 males and 65 females. Stature and weight were measured in a standard anatomical position in the Frankfurt Horizontal Plane with a stadiometer of 0.1 cm precision. Measurements of both feet's height, length, and breadth were taken using a Vernier caliper, osteometric board, and height scale. The data were analyzed using SPSS 26.00.Results It was observed that all foot dimensions in males were significantly larger than in females. Sex prediction using linear methods yielded an accuracy of 94.8%, with a stature estimation error of 4.15 cm. When employing Artificial Neural Networks, sex prediction accuracy increased to 97.8%, and the error in stature estimation was reduced to 4.07 cm.Conclusions Our findings indicate that Artificial Neural Networks can work more effectively with such data. Using Artificial Neural Networks, the accuracy of sex prediction for both feet exceeded 95%. Additionally, the error in stature estimation was reduced compared to the formulas obtained through linear methods.en_US
dc.identifier.doi10.1186/s41935-024-00391-4
dc.identifier.issn2090-536X
dc.identifier.issn2090-5939
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-85190813525en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org/10.1186/s41935-024-00391-4
dc.identifier.urihttps://hdl.handle.net/11616/101940
dc.identifier.volume14en_US
dc.identifier.wosWOS:001205270600001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInt Assoc Law & Forensic Sciencesen_US
dc.relation.ispartofEgyptian Journal of Forensic Sciencesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectSex determinationen_US
dc.subjectStature estimationen_US
dc.subjectLinear analysisen_US
dc.subjectArtificial neural networksen_US
dc.subjectForensic anthropologyen_US
dc.titleSex and stature estimation from anthropometric measurements of the foot: linear analyses and neural network approach on a Turkish sampleen_US
dc.typeArticleen_US

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