Blood Pattern Analysis: Insights and Advances in Forensic Science
Abstract
Blood pattern analysis (BPA) examines the characteristics and appearance of bloodstains to pinpoint the underlying physical processes. For an analyst to comprehend the events, bloodstain distribution patterns at the murder scene can be used to recreate an earlier event. It is possible to infer the impact velocity of each stain selected by the expert and estimate the volume of bloodstains from an actual impact pattern.
Several software applications help to provide more objectivity, reproducibility, and traceability to BPA. Professional training and experience help investigators make valid and accurate conclusions based on BPA evidence. To eliminate the inconsistencies in the definition and use of BPA terminology and categories, new standards can be created, and the existing ones can be improved.
Introduction
Blood is one of the most typical types of evidence found at a crime scene as its viciousness causes it to produce distinctive bloodstain patterns that, when examined, can depict possible crime scene events. Blood pattern analysis (BPA) examines the appearance and characteristics of bloodstains to identify the underlying physical processes. The method is used in crime scene investigations to provide details about what happened when the crime was committed. The knowledge of the region of origin—also referred to as the blood source—during the blood-shedding event aids the investigator in their investigation. Using this information to support or dispute claims made in court is crucial to prevent injustices from occurring.
Article 1 Overview: Singh et al. (2021)
Background
The article aims to learn about blood and BPA by examining how blood stains appear using Awlata or Alta, which is an Indian dye used by women for grooming. Singh et al. (2021) used the product to make fictitious bloodstains to investigate how bloodstains form in relation to different elevations. Singh et al. (2021) also aimed to search for a connection between satellite stains and bloodstains with spines and the influence of height. The researchers also described the different types of bloodstain patterns, including passive, spatter, and altered patterns. The patterns describe bloodstains formed by gravity, an attack by a hard object, and a possible physical exchange, respectively.
Summary and Findings
A systematic review of publications discussing BPA was used to perform the study. Using Awlata to simulate bloodstains, Singh et al. (2021) conducted additional research to understand better how stains are formed. The researchers used a fixed angle and varying height to collect data for the study. According to Singh et al. (2021), satellite stains that emerged from dropping fake blood stains at a greater distance were also being produced at higher heights of the fake blood. The experimental results indicated that satellite stains were negatively correlated with spine height and directly correlated with blood stain height.
Significance
Bloodstain distribution patterns at the crime scene can be used to reconstruct an earlier event for a better understanding of the crime event. A step-by-step process will make it easier to distinguish and examine distinct bloodstain patterns, and look for interesting details supporting the theory that blood patterns arise due to injuries. Case descriptions and comments (from witnesses or perpetrators) can clarify the course of events and require knowledge of injuries and casework experience for appropriate reconstruction. The researchers also wanted to validate the use of Awlata to examine bloodstains in future research undertakings.
Article 2 Overview: Laan et al. (2015)
Background
The study was conducted to assess the possibility of understanding bloodstain’s impact velocity and estimate their volume from an actual impact pattern. Laan et al. (2015) also wanted to demonstrate how their approach could help to calculate a blood droplet’s trajectory while considering drag and gravity. This would help to pinpoint the location of an impact pattern’s origin far more precisely and correctly. This would allow the investigator to locate the blood source in the room, link it to the victim’s position (such as standing or sitting), or establish a link between particular wounds and patterns.
Summary and Findings
The researchers conducted their study at the Netherlands Forensic Institute (NFI). They created eight bloodstain patterns one meter apart from the wall. Laan et al. (2015) located the origin of each pattern using the straight-line approximation, the gravity-only technique, and the gravity-and-drag method. The impact velocity and volume of each bloodstain were estimated using sophisticated fluid dynamics and a 3D scanner, respectively. They proved that the location of the origin can be established approximately four times more precisely by incorporating gravity and drag in the trajectory computation than by using the straight-line approximation.
Significance
The researchers believed the discovery would be precious to detectives who utilize BPA to piece together what happened at crime scenes. Analysts will be able to pinpoint the victim’s location more accurately. The findings also point to the possibility of linking specific bloodstain patterns to the site and height of particular body wounds. As a result, detectives can be able to identify whether the victim was standing or sitting and to link specific patterns of injuries on the body, which is crucial for crime scene reconstruction.
Article 3 Overview: Home et al. (2021)
Background
Software programs and other quantitative methods have been researched to enable investigations into some BPA components with greater objectivity, reproducibility, and traceability. Home et al. (2021) conducted a systematic evaluation to identify all software for digital AO analysis that was currently accessible. The study sought to ascertain the degree to which forensic standards, like the UK’s ANSI/ASB Standard 072, have been complied with in the literature (Home et al., 2021). Further, I thought about what additional work was needed to achieve the specifications for the BPA software application.
Summary and Findings
Through a systematic review, the researchers examined the breadth of experimental validation and casework applications of blood-drop trajectory analysis software. Peer-reviewed research and commercial websites produced between 1987 and 2020 comprised the 92 sources collected for the study (Home et al. (2021). According to Home et al. (2021), six of the 15 software programs identified during this analysis were proven to have been used in casework. Based on publicly accessible literature, it appears that the reviewed software does not entirely pass pertinent forensic validation standards.
Significance
The report thoroughly analyzes all available software alternatives for forensic investigators and bloodstain pattern analysts. It also reveals the breadth of studies conducted to validate these techniques and the reported uses of this software in criminal proceedings (Home et al., 2021). The documentation of available software and their application in cases may encourage other investigators to use the same approaches. The study helps to offer the necessary validation to ensure the evidence generated through software applications is admissible in court.
Article 4 Overview: Siu et al. (2017)
Background
Existing literature does not help to distinguish gunshot spatter from that produced by blunt instrument impacts. Theestablishment of the circumstances under which gunshot and blunt instrument spatter patterns can be accurately distinguishedis vital. Siu et al. (2017) claim that forensic science professionals have long wished for such distinctions to reduce ambiguity in categorizing small stain blood spatter patterns. They worked to create a quantitative methodology to help distinguish between spatter patterns caused by gunshot and blunt instrument hits.
Summary and Findings
The impact velocity of various caliber bullets and blunt objects was employed to create controlled spatter patterns, and data was collected using high-speed video. Siu et al. (2017) measured over 500,000 distinct stain sizes in 72 different spatter patterns. They found out that the average stain size produced by gunshot is about 30% lower than that of blunt instrument spatter (Siu et al., 2017).
However, blunt instrument spatter has a 400% higher value of f0.75, a spatially dependent metric for the fraction of droplets larger than 0.75 mm in diameter (Siu et al., 2017). Custom image analysis methodology provided prompt and automatic quantitative measurements of the size and spatial distributions of individual stain sizes inside a spatter pattern to further authenticate the findings.
Significance
The findings suggest that quantitative measurements based on the spatially dependent stain proportions within a spatter pattern can provide a more accurate and objective technique to differentiate between spatter patterns produced by gunshot or blunt instrument impact. However, more research should be done using different impact methodologies. The findings will help to see whether the mathematical methodology developed here can be used with different dynamic impact methodologies (Siu et al., 2017). Future improvements should provide a method for calculating the impact energy and bullet velocity loss when a bullet passes through any medium.
Article 5 Overview: Bettison et al. (2021)
Background
The reliability and admissibility of expert testimony involving BPA have drawn criticism for forensic science due to the impact on evidence presentation and evaluation in courtrooms. Bettison et al. (2021) sought to determine if prior BPA experience (including training) helps to recognize bloodstain patterns and other mechanisms of blood deposition correctly. The second goal was to evaluate how the experience affected the judiciary’s ability to get pertinent information. The study hoped to address some of the criticisms of BPA practitioner performance and expertise.
Summary and Findings
Bloodstain pattern categorization accuracy was evaluated for both expert practitioners and untrained non-practitioners who were required to examine bloodstain pattern photos by category and patterns. Trained professionals were able to distinguish among different bloodstain categories and patterns more accurately than non-practitioners when mandated to give only one response (p = 0.0001, p 0.00001, respectively) (Bettison et al., 2021).
Bettison et al. (2021) state that regardless of the response scenario, practitioner accuracy in bloodstain pattern recognition was consistently correlated with experience level (p = 0.0429). The results supported the hypothesis as expert analysts benefited from their training, casework experience, interaction with knowledgeable colleagues, and continued informal learning.
Significance
The major takeaway is that professional practitioners are more accurate than lay non-practitioners even at the broad category scale, and this gap expands further when considering the particular pattern type. There was also a noticeable rise in accuracy with experience, consistent with earlier studies that revealed that less experienced practitioners made more mistakes than older practitioners (Bettison et al., 2021). These findings strongly suggest that practitioners with little experience can make accurate and insightful assessments of the mechanisms underlying bloodstain deposition.
Article 6 Overview: Hicklin et al. (2021)
Background
BPA relies heavily on expert judgments, but the veracity and repeatability of their findings have never been thoroughly assessed. According to Hicklin et al. (2021), a 2009 assessment from the National Research Council of the National Academies harshly criticized BPA because of many uncertainties. Analysts of bloodstain patterns primarily provide personal verdicts rather than objective findings. In this work, the researchers aimed to evaluate the precision and reproducibility of judgments given by practicing BPA analyzers.
Summary and Findings
The findings of the background survey include the participants’ diversity in formal education, training, and experience. Hicklin et al. (2021) looked into the conclusions given by 75 practicing bloodstain pattern analysts for 92 bloodstain patterns, resulting in 33,005 responses to prompts and 1760 short text responses. They established that on samples with known causes, 11.2% of the replies were erroneous. 7.8% of responses were varied among the analysts, which demonstrated low reproducibility (Hicklin et al., 2021). The discrepancies regarding the definition and application of BPA nomenclature and classifications indicate the need for better standards.
Significance
The errors and conflicts in the terminology and categorizations of BPA may have significant consequences if they occur in casework. Hicklin et al. (2021) urge the BPA community, standards organizations, and laboratory management to consider the recommendations provided. The recommended actions fall into several broad categories, including the terms used, methods, lessons learned, and implications for casework. This will help to boost the exactness and reproducibility of BPA analysts’ findings.
Conclusion
BPA is essential in crime scene investigations, but its application needs to be revised due to several limitations, the worst of which is the subjectivity of the opinions provided by analysts instead of scientific findings. Most research articles analyzed seek to enhance the reliability, admissibility, and replication of BPA findings by proposing new approaches to conducting the analysis. Another major factor influencing the value of BPA evidence in a courtroom is the practitioner’s experience, which is vital in making important conclusions regarding the events at a crime scene.
References
Bettison, A., Krosch, M. N., Chaseling, J., & Wright, K. (2021). Bloodstain pattern analysis: Does experience equate to expertise? Journal of Forensic Sciences, 66(3). Web.
Hicklin, R. A., Winer, K. R., Kish, P. E., Parks, C. L., Chapman, W., Dunagan, K., Richetelli, N., Epstein, E. G., Ausdemore, M. A., & Busey, T. A. (2021). Accuracy and reproducibility of conclusions by forensic bloodstain pattern analysts. Forensic Science International, 325. Web.
Home, P. H., Norman, D. G., & Williams, M. A. (2021). Software for the trajectory analysis of blood-drops: A systematic review. Forensic Science International, 328. Web.
Laan, N., de Bruin, K. G., Slenter, D., Wilhelm, J., Jermy, M., & Bonn, D. (2015). Bloodstain Pattern Analysis: Implementation of a fluid dynamic model for position determination of victims. Scientific Reports, 5(1). Web.
Singh, P., Gupta, N., & Rathi, R. (2021). Blood pattern analysis—a review and new findings. Egyptian Journal of Forensic Sciences, 11(1). Web.
Siu, S., Pender, J., Springer, F., Tulleners, F., & Ristenpart, W. (2017). Quantitative differentiation of bloodstain patterns resulting from gunshot and blunt force impacts. Journal of Forensic Sciences, 62(5), 1166–1179. Web.