Chemiluminescence video assisted by chemometric modeling for forensic identification of blood at crime scenes

Abstract

The development of advanced chemiluminescent compounds and hematology methodologies has significant implications for forensic science, particularly for the detection of evidential residues at crime scenes. This study introduces a novel chemiluminescent (CL) method that utilizes a smartphone to produce digital videos of the chemiluminescent reaction between the luminol (5-amino-2,3-dihydrophthalazine-1,4-dione) reagent and blood. This innovative approach significantly reduces reagent consumption by 6 times, requiring less than 1 mL/0.01 g of sample/chemicals, which agrees with green chemistry principles. Blood samples used in this study were sourced from bovine liver and human subjects and were collected by the official forensic police at crime scenes. All samples were subsequently discarded by the criminal police. Frames from a 3-minutes video were processed using ImageJ software and the Color Grab app to generate RGB, HSV, and CMYK pattern recognition, combined with chemometric modeling. This enabled the differentiation of samples based on positive and negative patterns, effectively preventing false results. The pattern recognition models developed were able to distinguish bovine from human blood, even after dilution, which simulated attempts to hide traces at crime scenes through washing. The method demonstrated an accuracy of 90.30% with only four prediction errors and presented 100% sensitivity and specificity for the cotton + ceramics class, with 77.78% sensitivity and 93.10% specificity for both the wood and glass classes. Additionally, it was possible to estimate the age of the samples with a precision of 3.6 days. These results were obtained using a new data fusion strategy that facilitated the modeling of digital videos as a combination of frames to enhance model sensitivity and selectivity without increasing model complexity. These results indicate that the developed method is accurate, sensitive, and rapid. Supported by these results, this method represents a significant advancement in forensic science, offering a practical and efficient solution for crime scene investigations.