A mechanical device that uses gravitational and spring compression forces to create spatter patterns of known impact velocities is presented and discussed. The custom-made device uses either two or four springs (k₁ = 267.8 N/m, k₂ = 535.5 N/m) in parallel to create seventeen reproducible impact velocities between 2.1 and 4.0 m/s. The impactor is held at several known spring extensions using an electromagnet. Trigger inputs to the high-speed video camera allow the user to control the magnet’s release while capturing video footage simultaneously. A polycarbonate base is used to allow for simultaneous monitoring of the side and bottom views of the impact event. Twenty-four patterns were created across the impact velocity range and analyzed using HemoSpat. Area of origin estimations fell within an acceptable range (ΔX_av = 5.5 ± 1.9 cm, ΔY_av = 2.6 ± 2.8 cm, ΔZ_av = +5.5 ± 3.8 cm), supporting distribution analysis for the use in research or bloodstain pattern training. This work provides a framework for those interested in developing a robust impact device.

The intent of this study was to attempt to quantify error associated with the measurements required in area of origin reconstructions resulting from the analysis of blunt force impact patterns. Mathematical tables were constructed in order to examine trends associated with changing width and length ratios and the influence of impact angle change and area of convergence deviations. The analysis of the trends enabled informed stain selection, mitigating potential error. The analysis of the influence of stain measurement error and gamma angle error was conducted by reconstructing experimentally created blunt force impact patterns using the Tangent Method, comparing the resulting area of origin determinations to reconstructions generated using HemoSpat, a bloodstain pattern analysis software, and then isolating each variable in order to examine its effect on precision and accuracy.

A total of 10 blunt force impact patterns were created and initially analyzed utilizing the Tangent Method. The stains selected for the analysis of each pattern were input into HemoSpat software which generated separate and independent results, enabling a comparison of the absolute and relative error rates between the known area of origin and the two methodologies. This also provided a foundation for the examination of each variable’s contribution to absolute and relative error. Finally, artificially induced measurement error was generated by uniformly increasing and decreasing the length, width, and gamma angle values of the selected stains based on an absolute analysis of error. The deviation from the compared values was examined in order to determine if the resulting area of origin determination would adversely affect inferences related to scene analysis. The results indicate that the incorporation of measurement error into a reconstruction creates an error rate that would not substantively affect an area of origin determination or inferences which would typically be rendered based on that determination.

A recent article outlined methods for the comparison of nearly identical images. These included a byte-by-byte comparison using specialized software as well as a visual comparison by highlighting differences in pixels between the two images based on a threshold using Photoshop. This article presents an example of image comparison and proposes another, simpler solution, using software named Beyond Compare, that may be of interest to investigators.

Crime scene investigators generally have two options when they need to create a three-dimensional (3D) model of a crime scene: enlist the services of an expert 3D modeller who specializes in graphic modelling or learn one of the full-fledged modelling tools to create the model themselves. Many modelling tools have a very steep learning curve, so the time required to invest in learning a tool to get even a simple result is often prohibitive. In this article, we introduce SketchUp (version 8) as a relatively easy-to-use tool for modelling crime scenes in 3D, give an example of how the software can be applied, and provide resources for further information.

Impact blood stain patterns occur across a variety of violent crime scenes. In the hands of a trained bloodstain-pattern analyst, these patterns can provide a wealth of information that may be probative to the court. Unfortunately, trained bloodstain pattern analysts are not always on scene to capture the required information or guide the crime-scene investigator in deciding what stains and measurements to document. This creates a data disconnect that will eliminate the possibility for any future area-of-origin (AO) analysis effort. This article describes a documentation method for crime-scene investigators to bridge this disconnect and capture sufficient information for subsequent off-scene AO analysis.

Information gathered from cast-off patterns can be quite difficult to communicate to others who may not have attended the scene. An analyst at the scene can often visualize where in the room the person was standing when they were swinging the bloodied object that created the pattern as well as the approximate plane of motion of the swing. This information may be used as a limiting factor in their reconstruction, but the current methods of recording and conveying this information are limited. This paper demonstrates that more information can be gathered through an analysis of cast-off and describes a technique to record, analyze, and present this information to communicate it to others using a 3D software model.

In bloodstain pattern analysis, it is important to know the point of origin (PO) of an impact pattern. This point can be estimated by means of the stringing method, the tangent method, or by commercially available computer programs. In this study, the accuracy of two computer programs was investigated under different conditions. Impact patterns were created by means of a modified mouse trap, and subsequently the PO was calculated. By examining the characteristics of single bloodstains, the influence on the deviation could be determined. To improve the estimation of the PO, it is important to select bloodstains that lie close to the presumable location of the blood source, that are large (width >1.5 mm) and that show an elliptical form. If possible, bloodstains from different walls should be taken into account. Our recommendations may improve the PO determination of impact patterns.

It is common practice when calculating area of origin from impact spatter to use stains from both "sides" of the pattern ‐ stains to the left and to the right of the blood source. Impact spatter at crime scenes, however, often provides the analyst with bloodstain patterns that are not as pristine as those created in a controlled environment. One situation that may arise is impact spatter consisting of stains from only one side of the pattern because of the removal of an object after the impact, such as a door or a person, or because the stains from one side are not on a planar surface. This study looks at a method of calculating the area of origin using stains from only one side of the pattern and shows that these partial patterns may still provide usable calculations to determine the area of origin.

Determining the origin of impact patterns at crime scenes can be a challenge when there is limited or less-than-ideal information. This is made even more difficult if the analyst cannot incorporate data from nonorthogonal and orthogonal surfaces in the same analysis. Using HemoSpat software for impact pattern analysis allows analysts to remove several limitations, maximize the use of this information, and produce precise and reliable results.

The purpose of this study was to replicate the one performed in Further Validation of the BackTrack Computer Program for Bloodstain Pattern Analysis - Precision and Accuracy to validate the accuracy of the HemoSpat bloodstain analysis software against an accepted standard and to examine the reproducibility of the results. The Royal Canadian Mounted Police (RCMP) provided FORident Software the data for the 18 bloodstain targets from the original BackTrack study. The study of HemoSpat was initiated by FORident Software in October 2006, taken over by the RCMP in December 2006, and the analyses were completed in November 2007. The results show that the average distance from the known origin across patterns is in line with the original study. The standard deviations across patterns are well within the bounds laid out by the BackTrack study and shows that the results are reproducible given different analysts working with the same data.