Handheld hyperspectral imaging as a tool for the post-mortem interval estimation of human skeletal remains

Verena-Maria Schmidt; Philipp Zelger; Claudia Wöss; Margot Fodor; Theresa Hautz; Stefan Schneeberger; Christian Wolfgang Huck; Rohit Arora; Andrea Brunner; Bettina Zelger; Michael Schirmer; Johannes Dominikus Pallua

doi:10.1016/j.heliyon.2024.e25844

Handheld hyperspectral imaging as a tool for the post-mortem interval estimation of human skeletal remains

Heliyon. 2024 Feb 3;10(4):e25844. doi: 10.1016/j.heliyon.2024.e25844. eCollection 2024 Feb 29.

Affiliations

¹ Institute of Forensic Medicine, Medical University of Innsbruck, Muellerstraße 44, 6020 Innsbruck, Austria.
² University Clinic for Hearing, Voice and Speech Disorders, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria.
³ OrganLifeTM, Department of Visceral, Transplant and Thoracic Surgery, Medical University of Innsbruck, Innsbruck, Austria.
⁴ Institute of Analytical Chemistry and Radiochemistry, University of Innsbruck, 6020 Innsbruck, Austria.
⁵ Department of Orthopaedics and Traumatology, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria.
⁶ Institute of Pathology, Neuropathology, and Molecular Pathology, Medical University of Innsbruck, Muellerstrasse 44, 6020 Innsbruck, Austria.
⁷ Department of Internal Medicine, Clinic II, Medical University of Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria.

Abstract

In forensic medicine, estimating human skeletal remains' post-mortem interval (PMI) can be challenging. Following death, bones undergo a series of chemical and physical transformations due to their interactions with the surrounding environment. Post-mortem changes have been assessed using various methods, but estimating the PMI of skeletal remains could still be improved. We propose a new methodology with handheld hyperspectral imaging (HSI) system based on the first results from 104 human skeletal remains with PMIs ranging between 1 day and 2000 years. To differentiate between forensic and archaeological bone material, the Convolutional Neural Network analyzed 65.000 distinct diagnostic spectra: the classification accuracy was 0.58, 0.62, 0.73, 0.81, and 0.98 for PMIs of 0 week-2 weeks, 2 weeks-6 months, 6 months-1 year, 1 year-10 years, and >100 years, respectively. In conclusion, HSI can be used in forensic medicine to distinguish bone materials >100 years old from those <10 years old with an accuracy of 98%. The model has adequate predictive performance, and handheld HSI could serve as a novel approach to objectively and accurately determine the PMI of human skeletal remains.

Keywords: Deep learning; Digital image analysis; Handheld hyperspectral imaging; Human skeletal remains; Post-mortem interval.