Estimation of stature from hand and handprint dimensions in a Western Australian population

Determination of Mouth Width for Facial Reconstruction Based on Statistical Regression Model

INTRODUCTION

It is important to generate predictable statistical models by increasing the number of variables on the human skeletal and soft tissue structures on the face to increase the accuracy of human facial reconstructions. The purpose of this study was to determine mouth width 3-dimensionally based on statistical regression model.

MATERIAL AND METHODS

Cone-beam computed tomography scan data from 130 individuals were used to measure the horizontal and vertical dimensions of orbital and nasal structures and intercanine width. The correlation between these hard tissue variables and the mouth width was evaluated using the statistical regression model.

RESULTS

Orbital width, nasal width, and intercanine width were found to be strong predictors of the mouth width determination and were used to generate the regression formulae to find the most approximate position of the mouth.

CONCLUSION

These specific variables may contribute to improving the accuracy of mouth width determination for oral and maxillofacial reconstructions.

Prediction of Body Height Using Hand Length and Hand Breadth in Pharmacy and Nursing Students at Misrake Ghion College, Northeast Ethiopia: An Anthropometry Study

Objectives

To predict body height using hand length and hand breadth in pharmacy and nursing students at Misrake Ghion College, Northeast Ethiopia.

Methods

A cross-sectional prospective study was conducted from October 15 to January 20, 2021. The study was carried out on 316 students (160 males and 156 females). The study participants were from the Amhara ethnic groups, with the age range of 18 to 25 years. Body height, hand length, and hand breath were measured and analyzed using SPSS version 23. The strength of association was evaluated using correlation analysis. The significance level was set at p < 0.05. A paired sample t test was performed. Regression equations were derived using simple and multiple linear regression analysis.

Results

Hand length and hand breadth had a positive significant correlation with body height in both male and females. In both males and females, left hand length had a strong significant correlation (males r = 0.768, females r = 0.670), followed by right hand length (males r = 0.711, females r = 0.626). Regarding hand length, right hand breadth (males r = 0.671, female r = 0.438) and left hand length (males r = 0.504, females r = 0.525). There was a significant bilateral difference in hand length and hand breadth on its right and left sides (p < 0.05). Simple and multiple regression equations were formulated for each sex.

Conclusion

In both males and females, body height can be estimated from hand length and breadth using simple or multiple regression equations.

Estimation of Stature from foot length in male indigenous population of Assam Region

Human stature is one of the biological profiles that can and should be used in the identification of humans from different parts of the human skeleton. Estimation of stature from feet dimensions may play an important role in the identification process of a human. Further, it is also possible to establish a relationship between the feet dimensions and stature of a person. This study is focused on the measurements of feet dimension in indigenous population groups found in the North-East Indian Region (Assam). Measurements of the length of the foot and body height were carried out with the help of Vernier Calipers and standard measuring tape. This paper emphasizes the study of a total the number of 200 male bodies aged between 18 to 65. Linear correlation and regression equation were used to determine the correlation between the foot and body height and using Pearson's coefficient (ρ < 0.001) for the correlation between foot length and stature.

Stature estimation for Saudi men based on different combinations of upper limb part dimensions

Estimating stature based on body/limb parts can help define the characteristics of unidentified bodies. The most studied upper limb part is the hand, although few studies have examined whether stature can be estimated using fingers plus other hand dimensions. Moreover, there is paucity in anthropometric studies that determined whether bilateral whole limb parts (e.g., arms, forearms, and hands) are related to stature among the living subjects.This prospective cross-sectional study aimed to evaluate the relationship between different upper limb measurements and the stature of Saudi men. Furthermore, I assessed whether upper limb asymmetry was present, and developed regression models to estimate stature based on different available measurements. Stature and 13 upper limb parameters were measured for 100 right-handed Saudi men who were 18 to 24 years old.All measurements were positively correlated with stature (P < .001), and the best single predictor was the bilateral ulnar length. Asymmetry was more pronounced in the hand measurements. A multiparameter model provided reasonable predictive accuracy (±3.77-5.68 cm) and was more accurate than single-parameter models. Inclusion of the right-side fingers improved the model's accuracy.This study developed potential models for estimating stature during the identification of bodies of Saudi men.

Adjusted binary classification (ABC) model in forensic science: An example on sex classification from handprint dimensions

Binary classification techniques are commonly used in forensic examination to test if a specimen belongs to a particular group and base the expert opinion on the questioned evidence. However, most of the currently used methods do not achieve sufficient accuracy due to the ignoring of the specimens classified in the overlapping area. To address the issue, we proposed a novel Adjusted binary classification (ABC) algorithm that automatically adjusts posterior probabilities to reach classification accuracy and positive/negative predicted values (PPV, NPV) of 95 %. In the presented example, we used three handprint measurements from 160 participants (80 males and 80 females) to develop models that would classify sex from their dimensions. The sample was split into the training/cross-validated (70 %) and testing sample (30 %). We developed four classification models using linear discriminant analysis (LDA) by employing traditional single cut-off values and ABC approach that for each group provides a specific posterior probability cut-off threshold. In the cross-validated sample, the accuracy of traditional models was 78.7-92.5 %, while PPVs/NPVs ranged between 78.2 and 93 %. ABC models provided 95 % accuracy, PPV, and NPV, and could classify 35.5-88.1 % of specimens. In the testing sample, ABC models achieved accuracy of 97.3-100 %, PPV/NPV 95.4-100 %, and could be applied to 29.1-87.5 % of specimens. The study demonstrated that the ABC approach could adjust classification models to reach predefined values of accuracy, PPV, and NPV. Therefore, it could be an efficient tool for conducting a binary classification in forensic settings and minimizing the possibilities of incorrect classifications.

Stature estimation from handprint measurements: an application to the medicolegal investigation

Background

The estimation of the stature of human beings is a major part of medicolegal investigation when only body parts are found. The study aimed to estimate the stature from different handprint measurements in a Bangladeshi population using statistical considerations. A sample of 200 young Bangladeshi adults (100 men and 100 women) with no physical disabilities participated in this study. Stature and seven anthropometric measurements were measured using standard anthropometric measurements. The bilateral asymmetry was tested using the independent t test. The Pearson’s correlation coefficient (R) between the stature and different handprint measurements was calculated. Consequently, the simple and multiple linear regression models were developed to estimate the stature from the handprint measurements.

Results

The bilateral asymmetry was statistically not significant (p > 0.05) in right and left handprints. Sex difference significantly (p < 0.05) influences the relationship between stature and handprint measurements. A positive and strong coefficient of correlation (R) value presents between stature and the handprint measurements. The right 2^nd digit length in men (R = + 0.709, R² = 0.502, SEE = ± 44.141 mm) and the right handprint length in women (R = + 0.552, R² = 0.305, SEE = ± 49.074 mm) were the most reliable estimator of stature. However, when data were combined for both sexes, the right handprint length was identified as the most reliable estimator of stature with higher values of R (+ 0.777) and R² (0.603), and a lower value of SEE (± 55.520). Multiple regression equation showed greater reliability than linear regression equations in stature estimation from handprint measurements in Bangladeshi population.

Conclusions

It was concluded that the estimation of stature from handprint measurements is possible and reliable. The findings of this study are very useful from the forensic and medicolegal point of view and can use to estimate the stature in Bangladeshi population.

What can glove impression evidence reveal about assailants? A pilot study

Impressions and marks are expected components of any crime scene. There is nothing more disappointing for fingerprint experts than finding glove marks at a crime scene. The forensic expert’s primary task in such cases is to compare the characteristic features of glove impressions with the characteristics of a suspect. The aim of the present study was to determine whether additional information could be obtained from glove prints. Specifically, whether they could be used to help to predict the sex and stature of a suspect was investigated, as was the potential for ascertaining additional information in cases where such prints were recovered from diverse objects with different diameters. Male and female participants wore latex gloves, and after ink was applied to the gloves they grasped objects of different diameters (2, 4, 6 and 8 cm). Impressions of gloved flat hands were also obtained. Phalangeal and finger lengths were measured digitally via software. Sex and stature were successfully estimated based on impressions derived from gloved flat hands and from prints on various grasped objects. A regression equation was developed for stature prediction, and a discriminant equation was developed for sex prediction.

Different predictive and accuracy models for sex and stature estimation from second- and fourth-digit lengths in the Kinnaur population of Himachal Pradesh, North India: Medico-legal and forensic implications

Forensic anthropologists are not only active in courtroom testimonies but also contribute to disaster victim identification. The timely recovery and identification of victims in any disaster is crucial, and anthropologists play a vital role in this process. In mass disasters such as airplane crashes, tsunamis, earthquakes or terrorist attacks, fragments of dead bodies are usually brought for identification. Each fragment demands special tactics to fulfil any of the basic attributes of forensic identification such as age, sex, stature or ancestry. If sex and stature can be estimated from a single fragment, then it can potentially reduce the identification time and possible victim matches. In this study, an attempt has been made to estimate sex and stature from the second- and fourth-digit lengths. Different predictive and accuracy models have been devised using statistical techniques. No bilateral difference was observed in the digit lengths in either sex. Consequently, an average of the digit lengths was employed for model approximations. The fourth-digit length provided the best sex estimates (M=82.1%, F=79.2%) when binary logistic regression (BLR) statistics were applied. It was also observed that overall sex estimations improved from 78.8% (from BLR) to 79.8% when discriminant function analysis was used for sex estimation. Second- and fourth-digit lengths were used independently and together for stature estimation models for males and females individually and for the pooled sample. In stature estimation models, three major interpretations were perceived: (1) the second-digit length provided the best stature estimates; (2) the estimation models compute better stature estimates for females than their counterparts, that is, standard errors are less in females than males; and (3) second and fourth digits predict more reliable stature estimation when the sex of the digits is known than that of the pooled sample.

Stature estimation from hand anthropometric measurements in Bangladeshi population

The aim of this research was to generate a standard formula for estimating stature in the Bangladeshi population from hand anthropometric measurements. Arbitrarily selected a total of 150 male and 150 female healthy subjects within the age range 18-60 years participated in this study. Stature and nine hand parameters were taken using a standard tape and a digital slide calipers for each subject. The results indicate that in male Bangladeshi population, the bilateral variation of hand length, hand breadth, maximum hand breadth, palm length, thumb length, ring finger length, and little finger length was statistically not significant (p > 0.05). On the other hand, in female, bilateral difference of hand length, hand breadth, palm length, index finger length, middle finger length, ring finger length, and little finger length was statistically insignificant (p > 0.05). All hand dimensions were statistically significant (p < 0.001) and positively correlated with stature. Linear and multiple regression equation were used to estimate stature from hand anthropometric measurements. The accuracy of the determination of stature using hand dimensions ranged from ±3.688 to ±6.112 cm. Right-hand length was the most reliable single variable in both sexes in simple linear regression (SSE ±5.347 cm in male and ±3.688 cm in female). The multiple regression models were more reliable than the linear regression models as a lower SSE and higher R and R-square values. In conclusion, our present study has a great importance to estimate stature from hand measurements among Bangladeshis from the anatomical and forensic point of view.

Stature estimation from different combinations of foot measurements using linear and multiple regression analysis in a North Indian male population

Establishing the identity of the deceased is the most important task for forensic anthropologists in forensic case-work involving unidentified human remains. In such cases, forensic anthropologists examine the remains to derive the biological profile of the deceased i.e. estimation of age, sex, stature, and ethnicity to narrow down the search of the missing. Dismembered remains are recovered in mass disasters such as train mishaps, airplane crashes, earthquakes, and terrorists' attacks or in homicidal cases where perpetrator intentionally mutilates the dead body to conceal the identity of the victim. Stature estimation is considered as one of the most important tasks when a mutilated foot is recovered in process of narrowing down the pool of possible suspects/victims. Allometry is the underlying principle for estimation of stature from foot dimensions. It has been learnt from the published literature that multiple regression models including more than one factor enhances the estimation accuracies. Among the various foot dimensions, foot length is the most frequent parameter used in the estimation of stature in forensic literature. In the present study, an attempt has been made to standardize the stature estimation models from various possible combinations of foot dimensions. For this purpose, 388 Jatt Sikh males aged between 18 and 30 years were recruited from various villages of Ludhiana district of Punjab State in Northern India. Stature, five foot length measurements, and two foot breadth measurements were taken on each subject. Linear and multiple regression models were derived for the estimation of stature from various foot measurements. The highest coefficient of determination and estimation accuracy (the least standard error of estimation S.E.E) was observed from T1 (R² = 0.397, S.E.E = 4.7109) when a single foot dimension was included in the model, (R² = 0.416, S.E.E = 4.6425) from (T1, T3) when two-foot lengths were taken, (R² = 0.418, S.E.E = 4.6426) from (T1, T3, T4) when three-foot lengths were included, (R² = 0.418, S.E.E = 4.6473) from (T1, T3, T4, T5) when four-foot lengths were included, and (R² = 0.418, S.E.E = 4.6531) when all the five foot lengths (T1, T2, T3, T4, T5) were included in the regression model. It has been concluded that multiple regression models provide more accurate results than linear regression models. However, inclusion of a factor having a weak correlation with stature in the regression model, decreases the accuracy of the model.

Estimation of sex and stature using anthropometry of the upper extremity in an Australian population

Stature and a further 8 anthropometric dimensions were recorded from the arms and hands of a sample of 96 staff and students from the Australian National University and The University of Newcastle, Australia. These dimensions were used to create simple and multiple logistic regression models for sex estimation and simple and multiple linear regression equations for stature estimation of a contemporary Australian population. Overall sex classification accuracies using the models created were comparable to similar studies. The stature estimation models achieved standard errors of estimates (SEE) which were comparable to and in many cases lower than those achieved in similar research. Generic, non sex-specific models achieved similar SEEs and R² values to the sex-specific models indicating stature may be accurately estimated when sex is unknown.

Estimation of stature from hand and handprint measurements in Iban population in Sarawak, Malaysia and its applications in forensic investigation

Handprints and dismembered hands are commonly found during crime scene investigations and disaster victim identifications, respectively. It has been indicated that the accuracy of handprint and hand measurements for estimating stature maybe population specific. Since Iban is the largest ethnic population in Sarawak, Malaysia and because the application of anthropometry of hand and handprint within this population as well as other populations within the Southeast Asian countries remain unreported, this present study that investigated the reliability and accuracy of these two anthropometric aspects acquires forensic significance. Upon measuring the height, 21 measurements were recorded on each hand and the corresponding handprint of 50 male and 52 female consented adult Iban subjects. Using univariate statistics as well as simple and multiple regression analyses, interpretation of the measurements examined here was attempted. Results revealed that lengths of hand and handprint are the more reliable traits for estimating stature in both the male and female Iban subjects (p < 0.05) with correlation strength ranging from 0.60 to 0.76. Comparable to the established skeletal standards for hand, the stature prediction accuracy using hand and handprint measurements investigated in this research ranged between 4.29 and 5.78 cm. Hence, this research provided the first forensic standard for estimation of stature among the Iban population in Sarawak that may prove useful for crime scene investigations and disaster victim identifications in Malaysia.

Estimation of stature by using the dimensions of the right hand and right foot in Han Chinese adults

The Han Chinese people are the main ethnic group in China and the largest ethnic group in the world. The dimensions of the hands and feet have been successfully used for the estimation of stature. A total of 26,927 healthy adult subjects, comprising 13,221 men and 13,706 women, were recruited. The survey samples were chosen through random cluster sampling. The mean values were significantly higher in men than those in women for all measurements (P<0.001). All the measurements showed a statistically significant correlation with stature (P<0.01). The combination of the right hand length and the right foot length was the best predictor of stature because it had the lowest standard error of estimate. The use of multiple regression equations yielded better results than did the use of linear regression equations. The accuracy of stature prediction ranged from ±4.81 to ±6.39 cm. The present study was of great importance with regards to improving the physical anthropology database of ethnic groups in China.

Converging Evidence of Ubiquitous Male Bias in Human Sex Perception

Visually judging the sex of another can be achieved easily in most social encounters. When the signals that inform such judgements are weak (e.g. outdoors at night), observers tend to expect the presence of males-an expectation that may facilitate survival-critical decisions under uncertainty. The present aim was to examine whether this male bias depends on expertise. To that end, Caucasian and Asian observers targeted female and male hand images that were either the same or different to the observers' race (i.e. long term experience was varied) while concurrently, the proportion of targets changed across presentation blocks (i.e. short term experience change). It was thus found that: (i) observers of own-race stimuli were more likely to report the presence of males and absence of females, however (ii) observers of other-race stimuli--while still tending to accept stimuli as male--were not prone to rejecting female cues. Finally, (iii) male-biased measures did not track the relative frequency of targets or lures, disputing the notion that male bias derives from prior expectation about the number of male exemplars in a set. Findings are discussed in concert with the pan-stimulus model of human sex perception.

Estimation of stature from handprint dimensions in Egyptian population

Handprint in the scene of the crime is one of the most valuable clues in identification of the assailant. There are numerous studies on estimation of stature from direct measures of hand dimensions, but using a handprint instead, there is little research on it. So this study tried to focus on handprint as a tool used in estimation of stature. One hundred right male hands and 91 right female hands were scanned, processed via Photoshop program and handprint measurements were taken using a software program. Our results showed that stature could be estimated from handprint measurements by simple and multiple regression equations with standard error of estimate was the lowest in handprint length ±4.54 cm in male and ±5.38 cm in female. It was concluded that handprint from the scene of the crime could be used for the prediction of the stature of the assailant.

A study of the anthropometric correlations between upper limb measurements for personal identification in Sudanese population

The presence of multiple isolated commingled fleshed limbs or limb parts generates a significant challenge for forensic investigators in wars, mass disasters, and criminal assaults in the process of identification. Although upper limb measurements have been used to establish individual identity in terms of sex and stature with high success, there is a scarcity of data concerning the correlations within upper limb parts. Hence, this study aims to assess the relationships within upper limb parts and develop regression formulae to reconstruct the parts from one another. The study participants were 376 Sudanese adults (187 males and 189 females). The results of this study indicated significant sexual dimorphism for all variables. The results indicated a significant correlation within the upper limb parts. Linear and multiple regression equations were developed to reconstruct the upper limb parts in the presence of a single or multiple dimension(s) from the identical limb. Multiple regression equations generated better reconstructions than simple equations. These results are significant in forensics and orthopedic reconstructive surgery.

Estimation of stature from the upper limb measurements of Sudanese adults

The estimation of stature using different parts of the body is crucial for formulating a biological profile during the process of personal identification, especially when mutilated and amputated limbs or body parts are found. Hand anthropometry has been reported in the literature including limited range of populations to be promising for stature prediction, but few studies have attempted to link upper limb anthropometry to stature. No previous research on this topic has been reported for modern Sudanese adults. Therefore, the aim of this study was to assess the relationship between the upper limb dimensions and stature in Sudanese adults and to develop regression formulae to estimate stature from these dimensions. The stature, upper arm length, ulnar length, wrist breadth, hand length, and hand breadth of 200 right-handed subjects, comprising 100 males and 100 females (aged 25-30 years), were measured. Initially, the data were analyzed using basic univariate analysis and independent t-tests; then sex-specific simple and multiple linear regression models were used to estimate stature. The results indicated significant sexual dimorphism for all measurements. There was a positive correlation between upper limb measurements and stature (p<0.01), which was highest for ulnar length. The accuracy of stature prediction ranged from ±3.54 to 5.85 cm. The use of multiple regression equations gave better results than simple regression equations. This study provides new forensic standards for stature estimation from the upper limb measurements of Sudanese adults.