Forensic Identification Research Articles

Enhancing the Evidence with Algorithms: How Artificial Intelligence Is Transforming Forensic Medicine.

The integration of artificial intelligence (AI) into various fields has ushered in a new era of multidisciplinary progress. Defined as the ability of a system to interpret external data, learn from it, and adapt to specific tasks, AI is poised to revolutionize the world. In forensic medicine and pathology, algorithms play a crucial role in data analysis, pattern recognition, anomaly identification, and decision making. This review explores the diverse applications of AI in forensic medicine, encompassing fields such as forensic identification, ballistics, traumatic injuries, postmortem interval estimation, forensic toxicology, and more. A thorough review of 113 articles revealed a subset of 32 papers directly relevant to the research, covering a wide range of applications. These included forensic identification, ballistics and additional factors of shooting, traumatic injuries, post-mortem interval estimation, forensic toxicology, sexual assaults/rape, crime scene reconstruction, virtual autopsy, and medical act quality evaluation. The studies demonstrated the feasibility and advantages of employing AI technology in various facets of forensic medicine and pathology. The integration of AI in forensic medicine and pathology offers promising prospects for improving accuracy and efficiency in medico-legal practices. From forensic identification to post-mortem interval estimation, AI algorithms have shown the potential to reduce human subjectivity, mitigate errors, and provide cost-effective solutions. While challenges surrounding ethical considerations, data security, and algorithmic correctness persist, continued research and technological advancements hold the key to realizing the full potential of AI in forensic applications. As the field of AI continues to evolve, it is poised to play an increasingly pivotal role in the future of forensic medicine and pathology.

Linear Morphometric Analysis of Auricular Measurements of a Nigerian Igbo population

The human ear (auricle) is an important body component in biometric studies and forensic identification. The purpose of this study was to evaluate linear auricular morphometric measurements of a Nigerian Igbo population. 300 participants (142 males to 158 females) of at least 16 years of age were randomly recruited from settlements in the South-Eastern states of Nigeria. The participants were made to sit in a Frankfort horizontal position and auricular measurements such as total ear height (TEH), ear width (EW), lobule height (LH) and lobule width (LW) were obtained using a digital vernier caliper (validated by calibrating to 0.01mm). The ear index (EI) and lobule index (LI) were calculated using the measurements. Data obtained were analyzed using the Statistical Package for the Social Sciences (SPSS version 23.0). The following mean values were recorded for males: TEH [Right (R) = 47.01±6.30, Left (L) = 46.24±5.85], EW (R = 25.06±4.14, L = 24.68±4.32), LH (R = 13.92±2.61, L = 13.99±2.18), LW (R = 12.99±2.30, L = 13.30±1.94), EI (R = 53.47±7.23, L = 53.28±6.69) and LI (R = 95.17±18.12, L = 96.80±18.56); for females, TEH (R = 48.25±6.83, L = 48.25±6.24), EW (R = 25.19±3.93, L = 24.57±4.21), LH (R = 14.44±2.67, L = 14.89±2.55), LW (R = 13.37±2.26, L = 13.78±2.04), EI (R = 52.50±6.85, L = 50.93±7.05) and LI (R = 94.60±19.59, L = 94.30±16.63). Gender differences were highly significant regarding total ear height, lobular length and width, as well as the ear index of the left auricle. This study provides a baseline data for auricular morphometrics of adult Nigerian Igbos and could be used as an ergonomic guide towards the creation of hearing aids in the future and to solve possible forensic issues associated with identification of remains.

A morphometric approach to morphology analysis of palatal rugae in sibling groups.

Recent advances in imaging technologies, such as intra-oral surface scanning, have rapidly generated large datasets of high-resolution three-dimensional (3D) sample reconstructions. These datasets contain a wealth of phenotypic information that can provide an understanding of morphological variation and evolution. The geometric morphometric method (GMM) with landmarks and the development of sliding and surface semilandmark techniques has greatly enhanced the quantification of shape. This study aimed to determine whether there are significant differences in 3D palatal rugae shape between siblings. Digital casts representing 25 pairs of full siblings from each group, male-male (MM), female-female (FF), and female-male (FM), were digitized and transferred to a GM system. The palatal rugae were determined, quantified, and visualized using GMM computational tools with MorphoJ software (University of Manchester). Principal component analysis (PCA) and canonical variates analysis (CVA) were employed to analyze palatal rugae shape variability and distinguish between sibling groups based on shape. Additionally, regression analysis examined the potential impact of shape on palatal rugae. The study revealed that the palatal rugae shape covered the first nine of the PCA by 71.3%. In addition, the size of the palatal rugae has a negligible impact on its shape. Whilst palatal rugae are known for their individuality, it is noteworthy that three palatal rugae (right first, right second, and left third) can differentiate sibling groups, which may be attributed to genetics. Therefore, it is suggested that palatal rugae morphology can serve as forensic identification for siblings.

Mitochondrial DNA: From Forensic Genetics to the Origins of Humanity

Mitochondria are cellular organelles that provide cellular energy. Along with chloroplasts of plant cells, mitochondria are the only organelles that have genetic material. These peculiarities make mitochondrial DNA (DNA) one of the main research topics in the field of Cytology and Genetics. Interest shared by Criminalistics, which uses mDNA analysis for forensic identification of DNA traces in which nuclear DNA analysis is not possible. In addition to being used in forensic investigation, mtDNA analysis has also been widely used in paleoanthropological investigation through the elaboration of human phylogenies, which retroact to only one female ancestor, known as mitochondrial Eve. In this context, this manuscript aims to address the relevance of this organelle in the field of Criminalistics and the Sciences of Origins, presenting the scientific, philosophical and theological implications arising from the in-depth analysis of this cellular structure.

Hands-Free Analytical Urine Testing Technology Validated for Drug-Facilitated Crime Investigations.

Forensic laboratories need quick and simple technology to improve turnaround times, while delivering reliable results. The goal of this study is first to create a simplified workflow to meet new Academy Standards Board requirements for urine testing in drug-facilitated crime investigations and, second, to create "ready-to-go", "hands-free" testing technology to further streamline analytical procedures. A first of its kind, the ToxBox forensic test kit is used to validate a single analytical procedure for opioids, benzodiazepines, cannabinoids, antidepressants, and several other drug classes. Method performance indicators follow accreditation requirements and include accuracy, precision, measurement uncertainty, calibration models, reportable range, sensitivity, specificity, carryover, interference, ion suppression/enhancement, and analyte stability. "Hands-free" testing platforms require the use of new suspended-state technology to stabilize NIST-traceable standards premanufactured at precise concentrations in the presence of sample preparation reagents. By suspending all reaction components in the solid state, with air gaps between the phases, reference standards and process controls are built in a "ready-to-go" format and stabilized for long-term storage in the presence of a sample matrix, β-d-glucuronidase, and enzymatic buffers. "Hands-free" test kits are removed from storage, incubated at either ambient temperature or 60 °C, and assayed using validated methods. This is the first example of how complex forensic testing workflows can be streamlined with new "hands-free" testing strategies to meet analytical challenges associated with quantitative and confirmatory analyses.

Victim Notification Protocols for Untested Sexual Assault Kits: Survivors' and Advocates' Perspectives on Law Enforcement-Led Outreach Methods.

Current estimates suggest there are 300,000-400,000 untested sexual assault kits (SAKs) in police department storage facilities throughout the United States. As these kits are being discovered and then submitted for forensic DNA testing, legal system personnel may recontact victims. These "victim notifications" involve informing survivors their kits were previously untested, sharing the results of new DNA testing, and asking for their engagement in reinvestigating and prosecuting the case. Typically, victim notifications are conducted by police, and survivors are connected with victim advocates soon thereafter. In this study, we interviewed survivors about their experiences of being notified by the police. We also interviewed about their work supporting survivors. Both survivors and advocates expressed strong concerns about police conducting notifications without an advocate present.

Reproducibility of human landmark identification in morphological mandible prototypes: major parameters for a 3D CBCT approach.

The establishment of anthropometric measurements is of fundamental importance for the correct identification of human bodies. The objective of this study was to evaluate the accuracy and reliability of two-dimensional craniometric landmarks obtained from three-dimensional cone beam computed tomography reconstructions for forensic identification of humans. Computed tomography images with voxel sizes of 0.25, 0.3, and 0.4mm were obtained using i-CAT® three-dimensional equipment. Ten landmarks were randomly selected, and 10 measurements were demarcated in the three-dimensional reconstruction to evaluate the mandibular condyle, ramus, and body. This study demonstrated that protocols with voxels of 0.3mm should be preferentially indicated for the evaluation of linear and angular measurements. Implementing our methodology using prototypes for clinical and forensic simulations allows comparisons with human databases in identification issues.

The forensic information identification based on machine learning algorithms

Investigating crimes in selected areas, studying their occurrence and appropriate graphical visualization may be an important supportive information for police units. Nowadays, the available IT tools can improve the work of law enforcement agencies. For this purpose, in this work, we propose an exploration approach which allows for analyzing crime events that are recorded in the city of Baltimore, Maryland, USA. Based on the collected data, seven types of offenses are recorded. First, they are analyzed in terms of time verifying whether any type of event depends on the day of the week or a period of the day. Then the distribution of the crimes is examined by spatial clusterization and kernel density estimation methods. As a result of the analysis, it is shown when and where the citizens of the considered city are subject to the highest crime rate.

Artificial intelligence and skull imaging advancements in forensic identification

ABSTRACT Managing the massive losses associated with large-scale disasters requires significant resources. The unexpected violence of these events generally remains a matter of casualties that urgently need to be identified in a reliable and cost-effective manner. To overcome these difficulties, many researchers have attempted to develop automated methods; moreover, a few recent research have investigated the applicability of artificial intelligence (AI)-based methods using skull, dental, and maxillofacial forensic imaging. In this review, we speculate on the advancement and potential of AI in Dental and Maxillofacial imaging that can help simplify person or victim identification and speed up the process with good accuracy. Using a few prefix search phrases, an online literature search was conducted (AI, Forensic, Skull, Dental, Imaging, Radiology) to identify papers about the advancement of AI in forensic dentistry in all kinds of radiographs, including two-dimensional (2D) and three-dimensional (3D) radiographs, cone beam computed tomography (CT) and CT. Most of the studies reported that automated methods of human identification based on 2D and 3D Dental and Skull radiographs using a convolutional neural network showed to assist in the fast and accurate identification by expertise evaluating a lot of images and quickly coming up with potential matches for identification. We advocate the application of AI techniques in the identification of individuals. However, there is a need to continue research with emphasis to validate models in skull identification.

Safety Glove Detection Using Skin Impedance

At the time of surgery, the entire gloves will protect the surgeon from bloodborne antibodies and the surgical carving tools from bacteria on the skin of the physicians. However, glove prick is very common, and perforation rates are as high as 71%.When treating people with highly contagious diseases like HIV-AIDS, Hepatitis, there are extremely high chances of doctors being affected. This tool can be used for forensic investigations, laboratory testing, and other tasks in addition to performing surgical procedures. It can also be used by sewage cleaners. The goal of this project is to offer treatment to medical professionals who are exposed to numerous bacteria while performing procedures on patients. The doctors are alerted to the puncture by finding it in a glove, enabling them to take the appropriate action.

Application Progress of Objective Audiological Detection Techniques in Forensic Clinical Medicine.

The qualitative, quantitative, and localization analysis of hearing loss is one of the important contents of forensic clinical research and identification. Pure-tone audiometry is the "gold standard" for hearing loss assessment, but it is affected by the subjective cooperation of the assessed person. Due to the complexity of the auditory pathway and the diversity of hearing loss, the assessment of hearing loss requires the combination of various subjective and objective audiometric techniques, along with comprehensive evaluation based on the case situation, clinical symptoms, and other examinations to ensure the scientificity, accuracy and reliability of forensic hearing impairment assessment. Objective audiometry includes acoustic impedance, otoacoustic emission, and various auditory evoked potentials. The frequency-specific auditory brainstem response (ABR), 40 Hz auditory event related potential, and auditory steady-state response are commonly used for objective hearing threshold assessment. The combined application of acoustic impedance, otoacoustic emission and ABR can be used to locate hearing loss and determine whether it is located in the middle ear, cochlea, or posterior cochlea. This article reviews the application value of objective audiometry techniques in hearing threshold assessment and hearing loss localization, aiming to provide reference for forensic identification of hearing loss.

The Value of VR-PVEP in Objective Evaluation of Monocular Refractive Visual Impairment.

To study the virtual reality-pattern visual evoked potential (VR-PVEP) P100 waveform characteristics of monocular visual impairment with different impaired degrees under simultaneous binocular perception and monocular stimulations. A total of 55 young volunteers with normal vision (using decimal recording method, far vision ≥0.8 and near vision ≥0.5) were selected to simulate three groups of monocular refractive visual impairment by interpolation method. The sum of near and far vision ≤0.2 was Group A, the severe visual impairment group; the sum of near and far vision <0.8 was Group B, the moderate visual impairment group; and the sum of near and far vision ≥0.8 was Group C, the mild visual impairment group. The volunteers' binocular normal visions were set as the control group. The VR-PVEP P100 peak times measured by simultaneous binocular perception and monocular stimulation were compared at four spatial frequencies 16×16, 24×24, 32×32 and 64×64. In Group A, the differences between P100 peak times of simulant visual impairment eyes and simultaneous binocular perception at 24×24, 32×32 and 64×64 spatial frequencies were statistically significant (P<0.05); and the P100 peak time of normal vision eyes at 64×64 spatial frequency was significantly different from the simulant visual impairment eyes (P<0.05). In Group B, the differences between P100 peak times of simulant visual impairment eyes and simultaneous binocular perception at 16×16, 24×24 and 64×64 spatial frequencies were statistically significant (P<0.05); and the P100 peak time of normal vision eyes at 64×64 spatial frequency was significantly different from the simulant visual impairment eyes (P<0.05). In Group C, there was no significant difference between P100 peak times of simulant visual impairment eyes and simultaneous binocular perception at all spatial frequencies (P>0.05). There was no significant difference in the P100 peak times measured at all spatial frequencies between simulant visual impairment eyes and simultaneous binocular perception in the control group (P>0.05). VR-PVEP can be used for visual acuity evaluation of patients with severe and moderate monocular visual impairment, which can reflect the visual impairment degree caused by ametropia. VR-PVEP has application value in the objective evaluation of visual function and forensic clinical identification.

Construction and Application of Rib Fracture Diagnosis Model Based on YOLOv3 Algorithm.

The artificial intelligence-aided diagnosis model of rib fractures based on YOLOv3 algorithm was established and applied to practical case to explore the application advantages in rib fracture cases in forensic medicine. DICOM format CT images of 884 cases with rib fractures caused by thoracic trauma were collected, and 801 of them were used as training and validation sets. A rib fracture diagnosis model based on YOLOv3 algorithm and Darknet53 as the backbone network was built. After the model was established, 83 cases were taken as the test set, and the precision rate, recall rate, F1-score and radiology interpretation time were calculated. The model was used to diagnose a practical case and compared with manual diagnosis. The established model was used to test 83 cases, the fracture precision rate of this model was 90.5%, the recall rate was 75.4%, F1-score was 0.82, the radiology interpretation time was 4.4 images per second and the identification time of each patient's data was 21 s, much faster than manual diagnosis. The recognition results of the model was consistent with that of the manual diagnosis. The rib fracture diagnosis model in practical case based on YOLOv3 algorithm can quickly and accurately identify fractures, and the model is easy to operate. It can be used as an auxiliary diagnostic technique in forensic clinical identification.

Form follows function: Applying photographic content analysis to forensic firearm identification.

Drawing forensic conclusions from an image or a video is known as "photographic content analysis." It involves the analysis of an image, as well as objects, actions, and events depicted in images or video. In recent years, photographic depictions of objects suspected as illegal firearms have substantially increased, appearing on CCTV surveillance footage, captured by mobile phones and shared on social media. However, the law in Israel states that a person can be charged with illegally possessing a firearm only if it can be proven that the object is capable of shooting with lethal bullet energy. This becomes more challenging in cases where the firearm was not physically seized, and the evidence exclusively consists of images and video. In this study, photographic content analysis was applied to images and video where objects suspected as commercial or improvised firearms had been depicted. An image and event sequence reconstruction video databases of both firearms and replicas were created in order to better define firearm-specific functional morphological features. We demonstrate that it is possible to classify an object as a firearm by analyzing the functional, and not only the esthetic, morphology in images and video. It is also shown that event sequence reconstruction in video may be used to infer that an object suspected as a firearm has the capacity to shoot by confirming the occurrence of a shooting act or shooting process. Thus, photographic content analysis may be used to forensically establish that an object depicted in an image or a video is a firearm by ruling out other known scenarios, and without physically seizing it.

Photographic Identification of Tooth Prints After High Temperature Exposure

Tooth prints is a very potential tool in forensic identification as the enamel rod patterns on tooth surface is individually unique. This study was aimed to detect changes of tooth prints after teeth were exposed with high temperatures. Forty-five extracted teeth were divided into 5 groups, then exposed to various high temperatures for 15 minutes in a furnace. To ensure practical application, a highly reproducible digital photographic method to detect tooth prints was developed. Before and after the heating process, tooth prints were photographed. The image data was analysed using an open-source biometric software, and the number of matching points of each tooth was compared before and after treatment. Results showed the decreasing number of match points of tooth prints in accord with the increasing of temperature exposure (P &lt; 0.05). The number of tooth print matching points can be confidently observed at temperatures 600°C or lower. The consistence of matching points shows the prospect of tooth print analysis to become a reliable identification method. This digital photography technique offers a straightforward method for routine dental recording in daily practice by dentists and identification by forensic odontologists. It opens further direction for standardization of pattern analysis, database development, and daily protocols. Keywords: dental photography; forensic identification; high temperature; tooth prints

Highly sensitive nanozyme strip: an effective tool for forensic material evidence identification

Highly sensitive nanozyme strip: an effective tool for forensic material evidence identification

Development of a Multiplex Polymerase Chain Reaction Method for Rapid and Accurate Identification of Girella punctata and G. leonina (Teleostei: Girellidae)

Girella punctata and Girella leonina are economically important species found in the East Sea; along the southern coast of Korea; south of Hokkaido, Japan; around Taiwan; and in the East China sea. In Korea, these two species hold high value, particularly on Jeju Island. These species have similar appearances, and it is challenging to distinguish them, particularly during the seed period. We detected genetic differences in the mtDNA (COI gene) of G. punctata and G. leonina, which are morphologically indistinguishable, and developed species-specific genetic markers for their identification. In total, 16 and 4 haplotypes of the COI genes were obtained from G. punctata (n = 164) and G. leonina (n = 36), respectively. The haplotype diversity (Hd) and nucleotide diversity (Pi, %) of the COI were 0.359 and 0.054 for G. punctata and 0.560 and 0.078 for G. leonina, respectively. We designed a Girella species common primer (control) and species-specific primer sets (experimental) for the two species. Amplicon sizes of 991, 579, and 391 bp were obtained for common primers of the two Girella species G. punctata and G. leonina. To confirm multiple targets in a single reaction, multiplex PCR conditions were optimized to adjust its resolution and accuracy. The detection levels of the multiplex PCR were confirmed to be 0.01 ng/µL for the two Girella species. The multiplex PCR was not associated with cross-reactivity between G. punctata and G. leonina. This multiplex species-specific PCR method provides a simple and rapid technique for the identification of two Girella species, thus increasing the efficiency and quality of Girella species stock management and forensic identification to prevent species misidentification.

A human identification system for hair shaft using RNA polymorphism

Hair is one of the common pieces of evidence at crime scenes, with abundant mitochondrial DNA but limited nuclear DNA in its shaft. It also helps to narrow the investigation scope to maternal lineage but fails to provide unique individual information. We assumed that RNA in hair shafts would be an alternative resource used to perform human identification based on the facts that (1) RNA retains the polymorphic information; (2) the multi-copy of RNA in a cell resists degradation as compared to the one-copy of nuclear DNA. In this study, we explored the potential of RNA polymorphism in hair shafts for forensic individual identification. A SNaPshot typing system was constructed using 18 SNPs located on 11 genes (ABCA13, AHNAK, EXPH5, KMT2D, KRT35, PPP1R15A, RBM33, S100A5, TBC1D4, TMC5, TRPV2). The RNA typing system was evaluated for sensitivity, species specificity, and feasibility for aged hair samples. Hair samples from a Shanxi population in China were used for the population study of the system. The detection limit of the assay was 2 ng RNA. The CDP of these 11 genes was 0.999969 in the Shanxi population. We also identified the concordance of the RNA and DNA typing results. In summary, we developed an RNA typing method to perform human identification from hair shafts, which performed as accurately as nuclear DNA typing. Our method provides a potential basis for solving the human identification problem from hair shafts, as well as other biological materials that lack nuclear DNA.

Spectral non-destructive inspection of pigments via multivariate analysis

The inspection and identification of pigments is a critical task in forensic identification. Previously, investigators mainly analyzed them manually by comparing infrared spectra one by one, which was subject to significant subjective factors and time-consuming. This article proposes a non-destructive, fast, and accurate method for inspecting and identifying pigment evidence. In the experiment, 191 pigment samples from different brands were collected and analyzed for their infrared spectra. Multivariate scatter correction, Savitzky-Golay smoothing, and peak area normalization were used for preprocessing. Filter and multi-order derivative preprocessing were carried out, and feature extraction was performed using the CARS algorithm. Based on Fisher's discriminant, a classification model was established to distinguish between different brands of pigments accurately. The experimental results showed that infrared spectra combined with multivariate classification models could accurately identify pigment samples. The method was fast, non-destructive, and accurate, reducing inspection costs and improving efficiency. It can provide reference and guidance for inspecting and identifying relevant cases and other physical evidence inspections.

Designing an “Other Race Effect” test for forensic facial identification experts using the performance of deep networks and untrained humans.

Designing an “Other Race Effect” test for forensic facial identification experts using the performance of deep networks and untrained humans.