Software for the trajectory analysis of blood-drops: A systematic review

Home, Patrick H.; Norman, D; Williams, Mark A.

doi:10.1016/j.forsciint.2021.110992

Cited by 9 publications

(5 citation statements)

References 51 publications

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“…The systematic review published by Home et al. [28] highlighted the large range of accepted error rates that exist with BPA software for trajectory analysis, stating it can be difficult to compare accepted error rates between different software applications. The commonly reported error rates for BPA were considered as they relate to HemoSpat, FARO Scene, and FARO Zone 3D.…”

Section: Discussionmentioning

confidence: 99%

“…Specifically, this study revealed R3D would be highly beneficial to the practice of BPA for stains 50 cm or less from a wall, producing calculated AOs that do not differ significantly from the known coordinates of a blood source. The systematic review published by Home et al [28] highlighted the large range of accepted error rates that exist with BPA software for trajectory analysis, stating it can be difficult to compare accepted error rates between different software applications. The commonly reported error rates for BPA were considered as they relate to HemoSpat, FARO Scene, and FARO Zone 3D.…”

Section: F I G U R E 19mentioning

confidence: 99%

“…Adapted table from Home[28] outlining research as it relates to the current research study. Note the varying experimental conditions.…”

mentioning

confidence: 99%

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Assessing iPhone LiDAR & Recon‐3D for determining area of origin in bloodstain pattern analysis

Stevenson,

Liscio

2024

Journal of Forensic Sciences

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Bloodstain pattern analysis (BPA) has proven to be a useful tool in forensic and criminal investigations for quite some time. Traditionally, documenting a crime scene for a bloodletting event was completed using manual techniques, physical strings, and a tape measure. In more recent years, laser scanners and 3D software programs have become a preferred method to capture accurate data that improves the validity and reliability of BPA. The initial cost of laser scanning equipment is relatively high, rendering these systems inaccessible to some police and smaller agencies. Recon‐3D is a newly developed iPhone application that utilizes the iPhone LiDAR sensor in combination with video data to create 3D point clouds of crime scenes. To assess the viability of Recon‐3D for area of origin analysis, two tests were performed. One was a series of bloodstain impacts which were analyzed in FARO Zone 3D software, while the second was a series of 6 repeated Recon‐3D scans of two 90‐degree walls which was then compared to the FARO Focus S350 scanner using CloudCompare software. A total of eight impact patterns were made at three different distances from a wall. The area of origin was measured and compared to the known location of the blood source. The average total 3D error for the area of origin set at 25, 50, and 100 cm from two perpendicular walls was found to be 6.04, 15.16, and 36.59 cm, respectively. These results are similar to past studies where programs such as HemoSpat have been used. The results of the point cloud comparison show that on average, 95% of the points from Recon‐3D fall below a threshold of 3.6 mm when compared to a FARO Focus S350 laser scanner. Thus, the results of this test suggest that Recon‐3D is an accurate and affordable scanning application for bloodstain patterns at crime scenes and the data provide acceptable results for area of origin analysis in BPA programs which accept laser scanner data.

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Section: Discussionmentioning

confidence: 99%

Section: F I G U R E 19mentioning

confidence: 99%

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Assessing iPhone LiDAR & Recon‐3D for determining area of origin in bloodstain pattern analysis

Stevenson,

Liscio

2024

Journal of Forensic Sciences

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“…Three-dimensional models have also found applications in crime scene investigations that involve quantitative analysis. For instance, they have been utilized in bloodstain pattern analyses in 3D [134][135][136], crash and collision investigations [101,130,137] as well as bullet trajectory analysis [101,137]. These applications leverage the capabilities of 3D models to provide enhanced insights and quantitative data for a more comprehensive analysis of the crime scene.…”

Section: Future Directionsmentioning

confidence: 99%

A Virtual, 3D Multimodal Approach to Victim and Crime Scene Reconstruction

Villa,

Lynnerup,

Jacobsen

2023

Diagnostics

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In the last two decades, forensic pathology and crime scene investigations have seen a rapid increase in examination tools due to the implementation of several imaging techniques, e.g., CT and MR scanning, surface scanning and photogrammetry. These tools encompass relatively simple visualization tools to powerful instruments for performing virtual 3D crime scene reconstructions. A multi-modality and multiscale approach to a crime scene, where 3D models of victims and the crime scene are combined, offers several advantages. A permanent documentation of all evidence in a single 3D environment can be used during the investigation phases (e.g., for testing hypotheses) or during the court procedures (e.g., to visualize the scene and the victim in a more intuitive manner). Advanced computational approaches to understand what might have happened during a crime can also be applied by, e.g., performing a virtual animation of the victim in the actual context, which can provide important information about possible dynamics during the event. Here, we present an overview of the different techniques and modalities used in forensic pathology in conjunction with crime scene investigations. Based on our experiences, the advantages and challenges of an image-based multi-modality approach will be discussed, including how their use may introduce new visualization modalities in court, e.g., virtual reality (VR) and 3D printing. Finally, considerations about future directions in research will be mentioned.

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“…Additionally, the shape, size, and distribution of a blood spatter pattern can assist in reconstructing a crime scene (Lee et al 2020). Similarly, trajectory analysis of blood drops/spatter can offer a 'retrospective insight' into the spatial positioning of an injured party at the scene (Home et al 2021). As with fingermark analysis, blood spatter analysis requires a similar expert interpretation to elucidate the way the blood was generated (James et al 1999;Akin 2005 andBevel et al 2008).…”

Section: Introduction 11 Biological Properties Of Bloodmentioning

confidence: 99%

Refinement and validation of multi-source blood detection for operational use.

Kennedy¹

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The operational deployment of any technique in forensic casework must undergo thorough investigation of its capabilities and limitations. At Sheffield Hallam University for the past 14 years, the Francese Group have focused on developing the utilisation of Matrix Assisted Laser Desorption Ionisation Mass Spectrometry (MALDI MS) for forensic applications. Not only has this technique shown potential in several different areas (MALDI MS analysis of latent fingermarks, condom lubricants and drug detection in fingermarks and hair as some examples), also being deployed in casework, but in more recent years, the detection of blood also. The end users, namely police and forensic providers have shaped the programme of work on blood detection by letting priorities and needs drive the research. The validation studies conducted in this thesis offer evidence of robustness and versatility as well as further insights as to what circumstances MALDI MS would be most suited/needed for the investigation of blood at a sceneof a violent crime. Currently, crime scene investigators (CSI) and crime labs employ commercially available presumptive tests for the detection of blood when recovered from crime scenes. However, these tests are not specific and occasionally yield false positives. Furthermore, confirmatory testing is not routinely performed. The risk of a false positive result could potentially result in a wrongful conviction or dismissal in court and brings into question the validity of these tests when their findings are heavily relied on in judicial proceedings. The utilisation of MALDI MS Profiling (MSP) and MS Imaging (MSI) for the rapid and informative detection of blood in this thesis has shed light on the multiplex nature of this alternative approach. A great deal of the work presented has shown the capability to not only distinguish between human and animal blood, but to determine blood provenance down to the species level (Chapter 2). In terms of animal blood detection, even more intelligence has been gained within this strand of the project, highlighting that a distinction can be made between intravenous animal blood and traces of animal blood from packaged meat (Chapter 4). If animal blood was detected at a crime scene, being able to offer insight on the manner in how the blood was shed could offer considerable assistance in reconstructing the dynamics of the crime. The compatibility and robustness testing performed in this project, which has been demonstrated across several strands of the project (Chapters 2,3 and 5) has additionally shown that MALDI MS can be used in conjunction with several blood enhancement techniques (BET), deposition surfaces, in the co-presence of other biofluids, and in tandem with DNA typing post MALDI MSI analysis. This body of knowledge significantly contributes to further advance implementation of MALDI based approaches for the forensic analysis of blood in stains and fingermarks in an operational environment and to the further promotion of MALDI as a Category A technique in the Home Office Fingermark Visualisation Manual after its recent promotion to Category B.

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Software for the trajectory analysis of blood-drops: A systematic review

Cited by 9 publications

References 51 publications

Assessing iPhone LiDAR & Recon‐3D for determining area of origin in bloodstain pattern analysis

Assessing iPhone LiDAR & Recon‐3D for determining area of origin in bloodstain pattern analysis

A Virtual, 3D Multimodal Approach to Victim and Crime Scene Reconstruction

Refinement and validation of multi-source blood detection for operational use.

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