Forensic system to help tackle violence against women and girls

Forensic experts are developing a new system which could revolutionise how evidence is used in domestic violence and sexual assault cases.

Staffordshire University, the Forensic Capability Network (FCN) and Spectricon are leading a project which aims to improve the way forensic evidence is processed in criminal cases involving violence against women and girls (VAWG).

The end product will be a new system that dramatically improves the way these crimes are investigated by providing crucial information which could lead to more prosecutions.

Claire Gwinnett, Professor in Forensic and Environmental Science at Staffordshire University, explained: "We know that reports of VAWG crimes have increased, yet prosecutions remain incredibly low. In cases that involve strangers, forensic strategies can be used to link an offender to a crime with evidence such as DNA. However, in domestic violence cases it is often a partner or someone known to the victim who commits the crime which makes it harder to link forensic evidence to a specific incident.

"Because of this, such cases end up being based more on the credibility of the victim and the accused rather than using objective evidence. This means it is less likely to be taken to court and in turn leads to underreporting."

To try and combat this, the project will harness two proven technologies to create an automated system for the rapid recovery, classification, analysis and evaluation of trace evidence such as DNA and fibres.

The team will use Staffordshire University's patented Easylift forensic tape to recover large scale samples alongside Spectricon's SMMART microscope, which uses hyperspectral imaging and machine learning to autodetect forensic evidence.

Professor Gwinnett said, "Bringing together these technologies should enable us to map out large amounts of trace evidence which can help to reconstruct events. Source level evidence can be explained away in court because a victim and accused may live together, whereas activity level can reveal what took place and whose account it matches.

"For example, if someone came in contact with the neck region of a person, we would expect a higher number of fibres or DNA from that individual to be transferred and seen there."

She added: "This is not done currently is because it is time consuming and logistically not possible to manually identify trace evidence on this scale and find meaning in it. Using the SMMART microscope would automate the process and enable rapid analysis of these tapes."

Stakeholders from the criminal justice system who investigate VAWG crimes have been taking part in a series of workshops to help shape the project. Their feedback has been used to design a series of experiments which will focus on non-fatal strangulations.

Trained mixed martial artists have been enlisted for the upcoming experiments at Staffordshire University which will involve safely re-enacting common domestic violence scenarios and analysing trace evidence from their clothing.

This evidence will be used to develop an algorithm to apply the technique to VAWG cases and will be piloted within a UK police force later this year. The project, which will run until 2024, is funded by the government's Defence and Security Accelerator (DASA) and will ultimately lead to the creation of a triage toolkit for all police forces and forensic providers.

FCN's Director of Science, Vickie Burgin, said, "Violence against women and girls is a real priority for the forensic community, so this project is very exciting and we believe it will lead to significant improvements.

"Our expectation is that this will allow improved detection, leading to enhanced deterrence and, thereby, better security of those at risk of crimes of violence against women and girls. While such crimes will be our focus, the system that we will create will be of value in the detection all crime types in which the perpetrator is physically present at the crime scene."

Hear more about the research on Staffordshire University's YouTube channel.

Provided by Staffordshire University