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

The Precision of the Human Hand: Variability in Pinch Strength and Manual Dexterity

Changes in hand morphology throughout human evolution have facilitated the use of forceful pad-to-pad precision grips, contributing to the development of fine motor movement and dexterous manipulation typical of modern humans. Today, variation in human hand function may be affected by demographic and/or lifestyle factors, but these remain largely unexplored. We measured pinch grip strength and dexterity in a heterogeneous cross-sectional sample of human participants (n = 556) to test for the potential effects of sex, age, hand asymmetries, hand morphology, and frequently practiced manual activities across the lifespan. We found a significant effect of sex on pinch strength, dexterity, and different directional asymmetries, with the practice of manual musical instruments, significantly increasing female dexterity for both hands. Males and females with wider hands were also stronger, but not more precise, than those with longer hands, while the thumb-index ratio had no effect. Hand dominance asymmetry further had a significant effect on dexterity but not on pinch strength. These results indicate that different patterns of hand asymmetries and hand function are influenced in part by life experiences, improving our understanding of the link between hand form and function and offering a referential context for interpreting the evolution of human dexterity.

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.

Investigation on the Cooperative Grasping Capabilities of Human Thumb and Index Finger

The maximum cooperative grasping mass and diameter of the human thumb and index finger were investigated by 7560 grasp-release trials on various masses of solid cylinders and various sizes of rings. The maximum grasping mass of the participants’ thumb-index finger depended on gender, age and the sum of thumb-index finger lengths (P < 0.05), but not on the hand-used and ratio of index finger to thumb length (P > 0.05). The maximum grasping diameter of the participants’ thumb-index finger depended on the age, sum of thumb-index finger lengths and ratio of index finger to thumb length (P < 0.05), but not on the gender and hand-used (P > 0.05). There was a non-linear regression model for the dependence of the maximum grasping mass on gender, age and the sum of thumb-index finger lengths and another non-linear regression model for the dependence of the maximum grasping diameter on the age, sum of thumb-index finger lengths and ratio of index finger to thumb length. Two regression models were useful in the optimal size design of robotic hands intending to replicate thumb-index finger grasping ability. This research can help to define not only a reasonable grasp mass and size for a bionic robotic hand, but also the requirements for hand rehabilitation.

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.

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 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.

Determination of sex from various hand dimensions of Koreans

In the case of disasters or crime scenes, forensic anthropometric methods have been utilized as a reliable way to quickly confirm the identification of victims using only a few parts of the body. A total of 321 measurement data (from 167 males and 154 females) were analyzed to investigate the suitability of detailed hand dimensions as discriminators of sex. A total of 29 variables including length, breadth, thickness, and circumference of fingers, palm, and wrist were measured. The obtained data were analyzed using descriptive statistics and t-test. The accuracy of sex indication from the hand dimensions data was found using discriminant analysis. The age effect and interaction effect according to age and sex on hand dimensions were analyzed by ANOVA. The prediction accuracy on a wide age range was also compared. According to the results, the maximum hand circumference showed the highest accuracy of 88.6% for predicting sex for males and 89.6% for females. Although the breadth, circumference, and thickness of hand parts generally showed higher accuracy than the lengths of hand parts in predicting the sex of the participant, the breadth and circumference of some finger joints showed a significant difference according to age and gender. Thus, the dimensions of hand parts which are not affected by age or gender, such as hand length, palm length, hand breadth, and maximum hand thickness, are recommended to be used first in sex determination for a wide age range group. The results suggest that the detailed hand dimensions can also be used to identify sex for better accuracy; however, the aging effects need to be considered in estimating aged suspects.

Statistical sex determination from craniometrics: Comparison of linear discriminant analysis, logistic regression, and support vector machines

Accuracy of identification tools in forensic anthropology primarily rely upon the variations inherent in the data upon which they are built. Sex determination methods based on craniometrics are widely used and known to be specific to several factors (e.g. sample distribution, population, age, secular trends, measurement technique, etc.). The goal of this study is to discuss the potential variations linked to the statistical treatment of the data. Traditional craniometrics of four samples extracted from documented osteological collections (from Portugal, France, the U.S.A., and Thailand) were used to test three different classification methods: linear discriminant analysis (LDA), logistic regression (LR), and support vector machines (SVM). The Portuguese sample was set as a training model on which the other samples were applied in order to assess the validity and reliability of the different models. The tests were performed using different parameters: some included the selection of the best predictors; some included a strict decision threshold (sex assessed only if the related posterior probability was high, including the notion of indeterminate result); and some used an unbalanced sex-ratio. Results indicated that LR tends to perform slightly better than the other techniques and offers a better selection of predictors. Also, the use of a decision threshold (i.e. p>0.95) is essential to ensure an acceptable reliability of sex determination methods based on craniometrics. Although the Portuguese, French, and American samples share a similar sexual dimorphism, application of Western models on the Thai sample (that displayed a lower degree of dimorphism) was unsuccessful.

Estimation of sex from the metric assessment of digital hand radiographs in a Western Australian population

The forensic anthropologist is responsible for contributing to the identification of an unknown by constructing a biological profile from their skeletal remains. Towards achieving this goal, anthropologists can apply population and temporally specific standards with known error margins to morphometric data collected from a decedent. Recent research relating to the formulation of sex estimation standards has focussed on the assessment of bones other than the traditionally favoured pelvis and cranium, such as long bones of the appendicular skeleton. In particular, sex estimation standards based on morphometric data from metacarpals and phalanges have reported classification accuracy rates of 80% (and above) based on a narrow range of populations. The purpose of this study is to provide population-specific hand bone sex-estimation standards for a contemporary Western Australian population. The present study examines digital right hand radiographs of 300 adults of known age, equally represented by sex. A total of 40 measurements were taken in each hand (metacarpals and proximal phalanges); the measurements were then analysed using univariate statistics and cross-validated direct and stepwise discriminant function analysis. All hand bone measurements were significantly sexually dimorphic, with a tendency for the width measurements to express a higher degree of dimorphism than the length measurements. A maximum cross-validated classification accuracy of 91% was achieved with a sex bias of -6%. The standards presented here can be used in future forensic investigations that require sex estimation of hand bones in a Western Australian population.