ABSTRACT
Introduction The stature of an individual is an important parameter for establishing identification. The height of an individual can be indirectly estimated from different parts of the skeleton and such measurements are of great use in forensic science, anatomy, and anthropometry. This study was an attempt to formulate a linear regression equation for estimation of stature by measuring the ulnar length in the living adult Khasi population. Methods The study population consists of 164 subjects (Male: 118; Female: 46) between 25 and 45 years of age. The left and right ulnar lengths were measured from the tip of the olecranon process to the tip of the styloid process with the elbow flexed and palm spread over the opposite shoulder by a spreading caliper. The measurements of the stature of the volunteers were done in the standard anatomical standing position with a bared foot with the head in the Frankfort plane. The documented data were calculated by the standard statistical software. Results The height and ulnar length in males (160.85 ± 6.34 cm and 24.41 ± 1.10 cm, respectively) were found to be significantly (p < 0.001) higher than females (149.56 ± 2.95 cm and 22.58 ± 0.47 cm, respectively). Significant positive correlation coefficient (r) between height (cm) and ulnar length (cm) were observed in both males (r = 0.955, P < 0.001) and females (r = 0.915, P < 0.001), respectively. Conclusion The length of the ulna provides an accurate and reliable means in estimating the height of an individual; being almost a percutaneous bone, its length can be measured easily. The regression formulae that were derived in this study will be useful for clinicians, human anatomists, archeologists, anthropologists, and forensic experts.
ABSTRACT
Estimation of time since death (TSD) is an important aspect of forensic medicine. Methods used so far are subjective and have human errors. Corneal opacity images using software to analyze the red, green, and blue (RGB) components of corneal color against the TSD may prove to be an objective method. This study aimed to estimate TSD from image analysis of corneal opacity from the cornea of deceased individuals brought in for medicolegal autopsy to study the factors affecting corneal opacity and to formulate a predictive equation for the estimation of TSD. This was a cross-sectional study conducted at the department of forensic medicine and toxicology of a tertiary care medical institute over two years. The study group included cadavers brought in for autopsy where the TSD was known from hospital records. For study tools, we used a digital single-lens reflex (DSLR) camera with standardized settings, a dark box made of cardboard, and open-access RGB analysis software. Images were analyzed for differences in the numeric values of the RGB color and compared against the TSD. Correlations between TSD and age, gender, and environmental temperature were checked. This study involved 30 cases; these were analyzed and showed an increase in the numeric values of RGB for the corneal color as the TSD increases. Of note, the correlation of TSD with the color red was greater than for either blue or green; age had a positive correlation while gender had nearly no correlation, and the environmental temperature had a negative correlation. Based on this, gender was excluded from our equation. Also, we noted that the variance inflation factor of green was high and, therefore, excluded it from the predictive equation. The equation derived follows: TSD = {(0.091 x Age) + (0.171 x Red) + (0.018 x Blue) - (0.019 x Environmental Temperature) - 5.263}. Using this equation, the mean error was 21 minutes. This equation further narrowed the time range, usually given as four to six hours, when determining the TSD via conventional methods. Image analysis of corneal color after death using RGB analysis software can give us a more accurate and human error-free TSD that can be digitally stored and reproduced and, therefore, could prove useful in the forensic arena in the future.
