Department of Forensic Medicine, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Department of Biostatistics, Graduate School of Medicine, Hokkaido University, Sapporo, Japan.
Skin Res Technol. 2019 Jul;25(4):532-537. doi: 10.1111/srt.12683. Epub 2019 Feb 15.
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.
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.
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).
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.
先前的研究报告了皮肤的各种视觉参数与衰老引起的变化之间的关系。由于未识别尸体数量的增加,法医学领域预计将开发出一种快速估计年龄的方法。本研究测量了人体遗骸的各种皮肤视觉参数,并调查了这些参数与年龄之间的相关性。
对 414 例法医案例的四个身体部位(脸颊、下巴、臂部和大腿)拍摄了皮肤图像。我们从皮肤照片图像中解释了皮肤的八个视觉参数(平滑度、粗糙度、纹理、无光泽度、亮度、红斑、颜色阶段和下垂),并构建了三个按性别、死后间隔和年龄分类的年龄预测模型。
在使用三个模型计算的四个身体部位的视觉参数中,观察到脸颊和下巴的红斑、臂部的粗糙度以及臂部和大腿的纹理之间存在显著相关性。三个预测模型的均方根误差(表示模型精度)分别为 13.06、13.80 和 13.77。唯一与视觉参数相关的模型是性别(而不是年龄或死后间隔)。
与活体受试者一样,我们观察到一些视觉参数与年龄相关。与年龄相关的参数取决于所测量的部位是否暴露在阳光下。基于视觉参数的年龄估计需要测量暴露和不暴露于阳光的皮肤的视觉参数。