Age estimation based on visual parameters of the skin of cadavers

Abstract

Background Previous studies have reported relationships between various visual parameters of the skin and changes due to aging. Due to an increase in the discovery of unidentified bodies, the field of forensic medicine anticipates the development of a rapid method for estimating age. The present study measured various visual parameters of the skin in human remains and investigated the correlation between these parameters and age. Materials and Methods Skin images were taken of four body parts (cheek, chin, brachium, and thigh) of 414 forensic cases. We interpreted eight visual parameters of the skin (smoothness, roughness, texture, dullness, brightness, erythema, color phase, and sagging) from skin photograph images, and constructed three age‐prediction models, categorized by sex, postmortem interval, and age. Results Significant correlations were observed in the erythema of the cheek and chin, the roughness of the brachium, and the texture of the brachium and thigh among the visual parameters calculated in four body parts, using the three models. The root‐mean‐square errors, which indicate the precision of the three prediction models, were 13.06, 13.80, and 13.77. The only model that demonstrated a correlation with the visual parameters was sex (but not age or postmortem interval). Conclusion Similar to living subjects, we observed a correlation with age for a number of visual parameters. The parameters that correlate with age depend on whether the site being measured was exposed to sunlight. Age estimation based on visual parameters requires measurement of visual parameters for skin both exposed and not exposed to sunlight.

A Raman Algorithm to Estimate Human Age From Protein Structural Variations in Autopsy Skin Samples: the Proteins’ Biological Clock

“…Figure 3 also showed the predicted values of age and the 95% prediction intervals. [38][39][40][41][42] . Especially skin imaging and ultrasonography are very elementary and can be used by non-experts at scenes 38,41 .…”

Three-Dimensional Bioprinted Skin Microrelief and Its Role in Skin Aging

“…The key parameters that distinguish young and aged skin’s microreliefs are the length, depth, and area of each grid (or the angle number and maximum angle) [ 15 , 22 ]. The samples were created using the images of human skin of different age groups as shown in Figure 3 .…”

Estimativa de idade em indivíduos vivos

“…In older individuals, facial hair, and soft tissue, assessed by physical examination, contribute substantially to age estimation. The appearance of wrinkles and skin spots, hair thinning, baldness and the appearance of gray hair are phenomena related to aging and should be registered during the examination (Black, Aggrawal and Payne-James, 2010;Ichibori et al, 2014;Ramos and Miot, 2015;Ko, Korn and Kikkawa, 2017;Tsuboi et al, 2019;York et al, 2020). Some signs of senescence can also be seen in the eyes such as senile arch, dermatochalasis, pterygeum and pinguecola (Atchison et al, 2008;Deliaert et al, 2012;Grossniklaus et al, 2012;Jacobs et al, 2014;Song et al, 2017;Rezvan et al, 2018;Wanzeler et al, 2019).…”