Non-contact post-mortem interval determination
Posted on 21/06/2022
Leah S Wilk & Prof. Maurice Aalders
Presentation: "Non-contact post-mortem interval determination of human bodies using visible and thermal 3D imaging"
Location: online (Zoom)
Time and date: 29th June 7 - 8pm BST (8 - 9pm CET).
Please register by 28 June via this form (you will receive the link to the Zoom on the day of the lecture): https://forms.gle/ddNrr4a4Wa1XaQhVA
The postmortem interval (PMI) plays a key role in forensic investigations, as it aids in the reconstruction of the timeline of events. Currently, this information is provided by an empirical model (Henssge’s nomogram) describing postmortem body cooling. However, this model is subject to three significant limitations. First, the underlying experiments were conducted under standardized conditions, restricting applicability of the model to a specific subset of forensic cases. Second, in order to broaden this suitable subset, qualitative correction factors were introduced, rendering this approach subjective. Third, use of this model requires an invasive measurement of the victim’s core (rectal) temperature, risking contamination and destruction of other traces. Consequently, there is an urgent need to develop a non-subjective, widely applicable, and preferably non-invasive method for PMI estimation. To address this need, we developed a thermodynamic finite-difference algorithm, providing a rigorous method to simulate postmortem body temperatures. By combining this algorithm with photogrammetry and skin thermometry, we achieve accurate and non-invasive PMI estimation for bodies of arbitrary shape and posture. Moreover, using thermal imaging, this approach even allows non-contact PMI estimation. Finally, we extended the method’s applicability to cases where thermodynamic input parameters (e.g., ambient temperature) are unknown, by combining it with surrogate-model-based parameter optimization. Crucially, we validated this approach on deceased human bodies (both in the lab and at real crime scenes), and achieved the lowest PMI estimation errors to date (0.18h ±0.77h).
*Please note: Private recordings, screenshots or other types of recording by participants in the webinar are not permitted*