Highly sensitive and accurate estimation of bloodstain age using smartphone.

Biosens Bioelectron

School of Mechanical Engineering, Yonsei University, Seoul, Republic of Korea. Electronic address:

Published: April 2019

AI Article Synopsis

  • Estimating the age of bloodstains is crucial in forensic analysis, and a smartphone-based colorimetric system was previously developed for this purpose.
  • The current study improves sensitivity and accuracy by applying pattern recognition and classification techniques, utilizing three detection methods during different stages of the bloodstain drying process.
  • The system successfully determined bloodstain ages with a high level of precision (9 h, 18 h, and 48 h) by comparing bloodstain images to a database of reference images, promising advancements in real-time forensic science evaluations.

Article Abstract

The estimation of bloodstain age is an important factor in forensic analysis. Previously, we have reported a smartphone-based colorimetric system for age estimation of bloodstain, in which Whole blood and EDTA whole blood were dropped on 4 different materials (700 μL) and captured using a smartphone for 72 h. In order to enhance sensitivity and accuracy of the previous system, the current work is dedicated towards the application of pattern recognition and classification of bloodstain images based on a smartphone. Three detection methods (blood pool, crack ratio, and colorimetric analysis) in terms of 6 steps of drying process of the bloodstain (coagulation, gelation, edge desiccation, center desiccation, crack propagation, and final desiccation) were applied to estimate age of the bloodstain accurately. Three parameters from the bloodstain images were then classified as comparing to those of stored reference images with similar trends in database. The bloodstain age was successfully determined by 9 h, 18 h, and 48 h with respect to the three detection methods mentioned above, respectively. The differences in bloodstain images were clearly distinguished every hour by using smartphone-based pattern recognition analysis. Therefore, our system is expected to shed a light on the field of forensic science by estimating bloodstain age in real time.

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Source
http://dx.doi.org/10.1016/j.bios.2018.09.017DOI Listing

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