Optimizing sizing schedules of aircrew helmets using machine learning techniques

Introduction: Aircrew equipment assemblies are life critical equipment worn by the aircrew to ensure protection from various life-threatening environmental conditions that may occur in nominal or off-nominal flight conditions. It is important for the sizing system of body worn aircrew equipment to be divided into different size classes such that it is as representative of existing groups in the population as feasible. Machine learning techniques provide a powerful tool to develop efficient sizing systems that are representative of actual body types existing in the population. The objective of the study was to use machine learning clustering techniques to identify naturally existing body types to formulate an optimal sizing system for an aircrew helmet. Material and Methods: The standard sizing schedule of an aircrew helmet using head length and head breadth was studied. An iterative semi-supervised machine learning protocol called K-means clustering was used to identify naturally occurring clusters of head types within the population. The cluster boundaries were identified to develop the final sizing schedule. Analysis of variance (ANOVA) with post hoc analysis was carried out on the four head lengths and head breadths. Results: Four clusters of head type were identified using K-means clustering. This led to a sizing schedule which can be descriptively called “Short-Narrow,” “Short-Broad,” “Long-Narrow,” “Long-Broad.” ANOVA showed a statistically significant difference between the four clusters for both head length and head breadth. Conclusion: Consideration of several variables in sizing schedules often fails to meet desired fitment. Standard sizing methods use linear partitions on individual control parameters. In reality, the proportional variation between parameters is not linear. Machine learning tools help in identification of naturally occurring clusters within the database considering several variables at the same time. This study uses machine learning techniques to identify existing groups in a population and develop a final sizing schedule. Similar analysis for other aircrew equipment assemblies can be carried out to determine sizing schedules which assist in design and fitment.

Description of Cephalic Index in Female Indian and Chinese Malaysian

Cephalic index is an important parameter in evaluating racial and sexual differences, is measured by establishing a ratio between the breadth and the length of the head calculated as 100 times the maximum breadth of the head measured at the greatest diameter of the cranial vault above the supramastoid crest divided by the maximum length of the head measured from the most prominent point on the glabella to the opisthocranion. The aim of the research was to differentiate the cephalic index between female Indian and Chinese Malaysian studying in Padjadjaran University. This research was a descriptive study with total samples are 35 comprise of 13 females Indian and 22 females Chinese. The sampling technique used was stratified random sampling. The subjects were measured for head length and head breadth by using a spreading caliper. The result of the research shows that 22 female Chinese surveyed has an average cephalic index of 85.861(hyperbrachycephalic) with a standard deviation of 3.717. Meanwhile, the 13 female Indian surveyed has an average of 81.768 (brachycephalic), with a standard deviation of 3.205. The conclusion of this research is that there is a significant difference of cephalic index between females Indian and Chinese Malaysian.

Pattern of Cephalic Index among Medical Students of a Medical College of Eastern Nepal

Background Cephalic index (CI) is one of the important anthropometric parameters to determine racial variation. Studies done in Nepal has made a comparison of cephalic index for castes (Tharu, Brahmin, Chhetri, Newar), races (Mongoloids and Aryans) but lacks sex variation. The objective of this study was to find the difference in the cephalic index between two genders and to find the sequence of most predominant to least common head type in different genders among the Medical Students of Birat Medical College & Teaching Hospital (BMCTH). Methods A cross-sectional study conducted in the department of Anatomy of BMCTH from 1 July 2019 to 1 September 2019 comprising of 256 medical students (133 male and 123 female) aged between 18 to 24 years. Head length, head breadth and cephalic index were the variables measured using standard devices and techniques. Ethical clearance was taken from the Institutional Review Committee (IRC) of Birat Medical College & Teaching Hospital, Nepal. Results The mean cephalic index in male and female is found to be 81.41 ± 4.52 and 83.62 ± 4.08 respectively. Statistically significant difference found between gender in terms of head length males (18.78±0.69) and females (17.71 ± 0.60); head breadth males (15.28 ±0.62) and females (14.79 ±0.57). The mean cephalic index in males is 81.41 ± 4.52 varying from 69.31 to 94.48. In females, the cephalic index varied from 74.74 to 93.14 and the mean cephalic index is 83.62 ± 4.08. The difference between male and female cephalic index is found to be statistically significant. Majority (43.75%) had Brachycephalic head (CI>79.9) followed by Hyperbrachycephalic (26.95%), Mesocephalic (25.39%), and Dolicocephalic (3.90%). Conclusion Cephalic index is significantly high in female as compared to male whereas head length and breadth are significantly high in males than females. It confirms sexual dimorphism exists. Brachycephalic is the commonest head type.

A STUDY ON CEPHALIC INDEX OF ADULT NORTH INDIAN POPULATION

Introduction: Cephalic index is the percentage of head breadth to head length. The index is calculated from measurement of the diameters of head (head length and head breadth). When applied to living individuals it is known as cephalic index, and when referring to dry skulls, the cranial index. This index is used as a useful anthropological tool for analysis of racial and sexual differences in a population. The present study was done to find out Cephalic Index and to study sexual dimorphism in adult North Indian population. Objective of the study was to calculate the cephalic index and to find out that the present study group belongs to which category in the classification of skull based on cephalic index and to study the sexual dimorphism in respect to cephalic index. Material & Methods: The present study comprised of 200 medical students of age group between 18 yrs. to 25 yrs. of S.N. Medical College, Agra, not having any significant disease or deformity that could have affected the general or the bony growth. Two anthropometric parameters; head length and head breadth were recorded in centimeters by using spreading caliper. With these recorded data, cephalic index was calculated for males and females separately as well as combined. Results: Mean Cephalic Index was significantly higher (p=0.03124) in females (79.350 ± 5.7157) as compared to males (77.715 ± 4.9102). Conclusion: There was a statistically significant difference in the mean of the cephalic indices of male and female students (p=0.03124). The mean cephalic index of combined population in this study was 78.533 ± 5.3776 which states that the dominant head shape among North Indians is Mesaticephalic.

ESTIMATION OF STATURE FROM CEPHALIC DIMENSIONS IN A NIGERIAN POPULATION. Estimación de la estatura por las dimensiones cefálicas en una población nigeriana

Objetivos: El presente estudio trata de examinar la relación entre la estatura y dimensiones cefálicas en la etnia Igbo de Nigeria y proponer un modelo de regresión para estimar la estatura cuando las dimensiones cefálicas están disponibles. Materiales y Métodos: 500 sujetos (261 varones y 239 mujeres) de edades comprendidas entre 18 y 30 años, que vive en Nnewi, Nigeria, participaron en el estudio. La estatura y tres dimensiones cefálicas (longitud cabeza, amplitud cabeza y circunferencia de la cabeza horizontal) se tomaron de cada individuo. La estatura se tomó como la altura en posición de pie, y se midió (en centímetros) usando un metro de altura. La longitud de la cabeza fue tomada como la distancia occipito-frontal, y se midió (en centímetros) con un calibre deslizable Mitsutoyo. El tamaño de la cabeza fue tomada como la distancia máxima biparietal, y se midió (en centímetros) usando un calibre deslizante Mitsutoyo. Se midió la circunferencia horizontal de la cabeza (la distancia desde la glabela alrededor del cráneo de nuevo a la glabela) (en centímetros) usando una cinta métrica. Principales Resultados: Los resultados mostraron una correlación significativa de las dimensiones cefálicas con estatura en las mujeres (p<0,01). Para los varones, la circunferencia horizontal y la longitud de la cabezal tuvieron correlación significativa con la talla (p<0,05), mientras que la amplitud cabeza se correlacionó de manera insignificante (p>0,05). Las ecuaciones de regresión también se formularon para estimar la estatura de dimensiones cefálicas para sujetos masculinos y femeninos. Conclusión: El estudio mostró que la circunferencia horizontal y la amplitud de la cabeza es mejor predictor de la estatura que la longitud cefálica, y que las dimensiones cefálicas se puede utilizar para estimar la estatura. Objectives: The present study sought to examine the relationship between stature and cephalic dimensions in the Igbo ethnic group of Nigeria, and to propose a regression model for stature estimation when the cephalic dimensions are available. Materials and Methods: 500 subjects (261 males and 239 females) between the ages of 18 and 30, living in Nnewi, Nigeria, participated in the study. Stature and three cephalic dimensions (head length, head breadth and horizontal head circumference) were taken on each individual. Stature was taken as standing height, and was measured (in centimeters) using a height meter. Head length was taken as the occipito-frontal distance, and was measured (in centimeters) with Mitsutoyo sliding calipers. Head breadth was taken as the maximum biparietal distance, and was measured (in centimeters) using Mitsutoyo sliding calipers. Horizontal head circumference (the distance from the glabella around the cranium back to the glabella) was measured (in centimeters) using a metric tape. Main Results: The results showed significant correlation of cephalic dimensions with stature in the females (p<0.01). For the male subjects, horizontal head circumference and head length had significant correlation with stature (p<0.05) while head breadth was insignificantly correlated (p>0.05). Regression equations were also formulated for estimating stature from cephalic dimensions for the male and female subjects. Conclusion: The study showed that horizontal head circumference and head breadth were better predictors of stature than head length, and that the cephalic dimensions can be used to estimate stature.