The age-at-death estimation thresholds have recently been shifted towards a more objective assessment of the aging process. Such a non-subjective approach offers quantitative methods of age estimation; for instance, the method relating to the surfaces of pubic symphyses of males published by Stoyanova et al. (J Forensic Sci 62:1434-1444, 2017). A validation study was conducted to test the method performance in European samples. The sample consisted of 96 meshes of pubic symphyses of male individuals (known sex and age) that came from four different samples (two Portuguese collections, one Swiss, and one Crete). Stoyanova's method based on five regression models (three univariate and two multivariate models) performed worse in our sample, but only when the whole sample (without age limitation) was included. A sample limited to individuals under 40 years of age achieved better results in our study. The best results were reached through the thin plate spline algorithm (TPS/BE) with a root mean square error of 5.93 years and inaccuracy of 4.47 years. Generally, the multivariate regression models did not contribute to better age estimation. In our sample in all age categories, age was systematically underestimated. The quantitative method tested in this study works best for individuals under 40 years of age and provides a suitable basis for further research.
Forensic anthropology has developed classification techniques for sex estimation of unknown skeletal remains, for example population-specific discriminant function analyses. These methods were designed for populations that lived mostly in the late nineteenth and twentieth centuries. Their level of reliability or misclassification is important for practical use in today's forensic practice; it is, however, unknown. We addressed the question of what the likelihood of errors would be if population specificity of discriminant functions of the tibia were disregarded. Moreover, five classification functions in a Czech sample were proposed (accuracies 82.1-87.5 %, sex bias ranged from -1.3 to -5.4 %). We measured ten variables traditionally used for sex assessment of the tibia on a sample of 30 male and 26 female models from recent Czech population. To estimate the classification accuracy and error (misclassification) rates ignoring population specificity, we selected published classification functions of tibia for the Portuguese, south European, and the North American populations. These functions were applied on the dimensions of the Czech population. Comparing the classification success of the reference and the tested Czech sample showed that females from Czech population were significantly overestimated and mostly misclassified as males. Overall accuracy of sex assessment significantly decreased (53.6-69.7 %), sex bias -29.4-100 %, which is most probably caused by secular trend and the generally high variability of body size. Results indicate that the discriminant functions, developed for skeletal series representing geographically and chronologically diverse populations, are not applicable in current forensic investigations. Finally, implications and recommendations for future research are discussed.
Age-at-death estimation of adult skeletal remains is a key part of biological profile estimation, yet it remains problematic for several reasons. One of them may be the subjective nature of the evaluation of age-related changes, or the fact that the human eye is unable to detect all the relevant surface changes. We have several aims: 1) to validate already existing computer models for age estimation; 2) to propose our own expert system based on computational approaches to eliminate the factor of subjectivity and to use the full potential of surface changes on an articulation area; and 3) to determine what age range the pubic symphysis is useful for age estimation. A sample of 483 3D representations of the pubic symphyseal surfaces from the ossa coxae of adult individuals coming from four European (two from Portugal, one from Switzerland and Greece) and one Asian (Thailand) identified skeletal collections was used. A validation of published algorithms showed very high error in our dataset – the MAE ranged from 16.2 and 25.1 years. Two completely new approaches were proposed in this paper: SASS (Simple Automated Symphyseal Surface-based) and AANNESS (Advanced Automated Neural Network-grounded Extended Symphyseal Surface-based), whose MAE values are 11.7 and 10.6 years, respectively. Lastly, it was demonstrated that our models could estimate the age-at-death using the pubic symphysis over the entire adult age range. The proposed models offer objective age estimates with low estimation error and are able to estimate the age using the pubic symphysis across the entire adult age range.
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