Exploring the relationship between stride, stature and hand size for forensic assessment

• Published in: Journal of forensic and legal medicine Vol. 52; pp. 46 - 55
• Main Authors: Guest, Richard, Miguel-Hurtado, Oscar, Stevenage, Sarah, Black, Sue
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.11.2017
• Subjects: Biometric Identification - methods; Body Height; Female; Forensic Sciences; Gait; Hand - anatomy & histology; Humans; Image Processing, Computer-Assisted; Logistic Models; Male; Pathology; Walking Speed
• ISSN: 1752-928X; 1878-7487; 1878-7487
• DOI: 10.1016/j.jflm.2017.08.006

Forensic evidence often relies on a combination of accurately recorded measurements, estimated measurements from landmark data such as a subject's stature given a known measurement within an image, and inferred data. In this study a novel dataset is used to explore linkages between hand measurements, stature, leg length and stride. These three measurements replicate the type of evidence found in surveillance videos with stride being extracted from an automated gait analysis system. Through correlations and regression modelling, it is possible to generate accurate predictions of stature from hand size, leg length and stride length (and vice versa), and to predict leg and stride length from hand size with, or without, stature as an intermediary variable. The study also shows improved accuracy when a subject's sex is known a-priori. Our method and models indicate the possibility of calculating or checking relationships between a suspect's physical measurements, particularly when only one component is captured as an accurately recorded measurement. •A novel dataset to explore linkages between hand, stature, leg and stride measures.•The use of an automated system for the measurement of anatomical lengths.•We show the ability to predictively model relationships between measures.•We indicate the possibility of calculating or checking relationships for forensic use.