کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
95091 160414 2016 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Selecting best-fit models for estimating the body mass from 3D data of the human calcaneus
ترجمه فارسی عنوان
انتخاب بهترین مدل های مناسب برای برآورد توده بدن از داده های 3D از پاشنه انسان
کلمات کلیدی
پاشنه؛ برآورد توده بدن. تمام ممکن رگرسیون؛ مدل سه بعدی؛ جمعیت کره ای؛ پزشکی قانونی داده انسان شناسی جمعیت
موضوعات مرتبط
مهندسی و علوم پایه شیمی شیمی آنالیزی یا شیمی تجزیه
چکیده انگلیسی


• Best-fit models for predicting the body mass from the human calcaneus is developed.
• Load arm of the calcaneus are strongly correlated with the body mass statistically.
• The all-possible-regressions offer constant predictive accuracy in forensic study.

Body mass (BM) estimation could facilitate the interpretation of skeletal materials in terms of the individual's body size and physique in forensic anthropology. However, few metric studies have tried to estimate BM by focusing on prominent biomechanical properties of the calcaneus. The purpose of this study was to prepare best-fit models for estimating BM from the 3D human calcaneus by two major linear regression analysis (the heuristic statistical and all-possible-regressions techniques) and validate the models through predicted residual sum of squares (PRESS) statistics. A metric analysis was conducted based on 70 human calcaneus samples (29 males and 41 females) taken from 3D models in the Digital Korean Database and 10 variables were measured for each sample. Three best-fit models were postulated by F-statistics, Mallows’ Cp, and Akaike information criterion (AIC) and Bayes information criterion (BIC) for each available candidate models. Finally, the most accurate regression model yields lowest %SEE and 0.843 of R2. Through the application of leave-one-out cross validation, the predictive power was indicated a high level of validation accuracy. This study also confirms that the equations for estimating BM using 3D models of human calcaneus will be helpful to establish identification in forensic cases with consistent reliability.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Forensic Science International - Volume 262, May 2016, Pages 37–45
نویسندگان
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