Evaluating the utility of time-lapse imaging in the estimation of post-mortem interval: An Australian case study

Alyson Wilson, Stan Serafin, Dilan Seckiner, Rachel Berry, Xanthé Mallett

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
100 Downloads (Pure)

Abstract

Estimating post-mortem interval is an important aspect in forensic investigations. The aim of this study was to investigate if time-lapse imaging can be used to improve estimates of post-mortem interval using Megyesi et al.‘s [1] method for a human donor decomposing in an Australian environment. To achieve this, time-lapse images were taken every 30 min over a 6-month period. The Megyesi et al. [1] total body score (TBS) system was used to quantify the level of decomposition of the donor for each image. Linear regression was performed to determine if observing decomposition more than once a day leads to increased accuracy in predicting PMI (post-mortem interval). Decomposition initially progressed quickly and then plateaued at 1004 hours PMI, with a TBS of 24. Individual timestamps were created from the time-lapse images taken each day at 08:00 hrs, 11:00 hrs, 14:00 hrs, 15:00 hrs, and 17:00 hrs. All timestamps produced R2 values > 0.80, indicating that the Megyesi et al. [1] method accurately predicts PMI for this donor. The 08:00 hrs timestamp had the highest value R2 = 0.886, whilst the combined timestamp (which included the scores from all five images for each 24-hour period) R2 = 0.823 was the lowest. This study supports the validity of Megyesi et al.‘s [1] TBS model to estimate PMI. Two other interesting findings were that the results suggest that scoring TBS multiple times per day does not improve estimates of PMI, however scoring TBS at daybreak produces more accurate results than scoring TBS later in the day. This may be an important consideration in forensic scenarios.

Original languageEnglish
Pages (from-to)204-210
Number of pages7
JournalForensic Science International: Synergy
Volume1
DOIs
Publication statusPublished - 17 Aug 2019

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