Estimation of stature from static and dynamic footprints

Area of Science:

• Forensic Science
• Anthropometry
• Biomechanical Analysis

Background:

• Stature estimation is vital in forensic identification.
• Previous studies used various foot dimensions with limited anatomical linkage.
• A need exists for robust methods linking foot morphology to stature prediction.

Purpose of the Study:

• To investigate the correlation between specific foot measurements and stature.
• To identify reliable anatomical landmarks for stature estimation from footprints.
• To develop accurate regression models for stature prediction using footprint data.

Main Methods:

• Collected static and dynamic footprints from 61 UK adult participants.
• Digitized footprints and analyzed twelve length, width, and angle measurements.
• Employed linear regression and collinearity statistics to assess predictive power.

Main Results:

• Heel to fourth toe length (static) and heel to fifth toe length (dynamic) showed highest correlations with stature (r=0.786 and r=0.858, respectively).
• Heel to fifth toe length in dynamic prints was found to be an independent predictor.
• The best regression model achieved a standard error of estimate (SEE) of 4.16 and R(2) of 0.74.

Conclusions:

• The lateral border of the foot, particularly heel to fifth toe length, is a stable indicator for stature estimation.
• Calc_A4 and Calc_A5 length measurements are recommended for forensic stature estimation from footprints.
• This study provides an anatomical basis for the efficacy of lateral foot measurements in stature prediction.