Engineering topics
Young, Karen S.
Publications and source records attributed to Young, Karen S..
A Parametric Model of Shoulder Articulation for Virtual Assessment of Space Suit Fit
Shoulder injury is one of the most severe risks that have the potential to impair crewmembers' performance and health in long duration space flight. Overall, 64% of crewmembers experience shoulder pain after extra-vehicular training in a space suit, and 14% of symptomatic crewmembers require surgical repair (Williams & Johnson, 2003). Suboptimal suit fit, in particular at the shoulder region, has been identified as one of the predominant risk factors. However, traditional suit fit assessments and laser scans represent only a single person's data, and thus may not be generalized across wide variations of body shapes and poses. The aim of this work is to develop a software tool based on a statistical analysis of a large dataset of crewmember body shapes. This tool can accurately predict the skin deformation and shape variations for any body size and shoulder pose for a target population, from which the geometry can be exported and evaluated against suit models in commercial CAD software. A preliminary software tool was developed by statistically analyzing 150 body shapes matched with body dimension ranges specified in the Human-Systems Integration Requirements of NASA ("baseline model"). Further, the baseline model was incorporated with shoulder joint articulation ("articulation model"), using additional subjects scanned in a variety of shoulder poses across a pre-specified range of motion. Scan data was cleaned and aligned using body landmarks. The skin deformation patterns were dimensionally reduced and the co-variation with shoulder angles was analyzed. A software tool is currently in development and will be presented in the final proceeding. This tool would allow suit engineers to parametrically generate body shapes in strategically targeted anthropometry dimensions and shoulder poses. This would also enable virtual fit assessments, with which the contact volume and clearance between the suit and body surface can be predictively quantified at reduced time and cost.
A Parametric Model of Shoulder Articulation for Virtual Assessment of Space Suit Fit
Suboptimal suit fit is a known risk factor for crewmember shoulder injury. Suit fit assessment is however prohibitively time consuming and cannot be generalized across wide variations of body shapes and poses. In this work, we have developed a new design tool based on the statistical analysis of body shape scans. This tool is aimed at predicting the skin deformation and shape variations for any body size and shoulder pose for a target population. This new process, when incorporated with CAD software, will enable virtual suit fit assessments, predictively quantifying the contact volume, and clearance between the suit and body surface at reduced time and cost.
Relating Linear and Volumetric Variables Through Body Scanning to Improve Human Interfaces in Space
Designing space suits and vehicles for the diverse human population present unique challenges for the methods of traditional anthropometry. Space suits are bulky and allow the operator to shift position within the suit and inhibit the ability to identify body landmarks. Limited suit sizing options also cause variability in fit and performance between similarly sized individuals. Space vehicles are restrictive in volume in both the fit and the ability to collect data. NASA's Anthropometric and Biomechanics Facility (ABF) has utilized 3D scanning to shift from traditional linear anthropometry to explore and examine volumetric capabilities to provide anthropometric solutions for design. Overall, the key goals are to improve the human-system performance and develop new processes to aid in the design and evaluation of space systems. Four case studies are presented that illustrate the shift from purely linear analyses to an augmented volumetric toolset to predict and analyze the human within the space suit and vehicle. The first case study involves the calculation of maximal head volume to estimate total free volume in the helmet for proper air exchange. Traditional linear measurements resulted in an inaccurate representation of the head shape, yet limited data exists for the determination of a large head volume. Steps were first taken to identify and classify a maximum head volume and the resulting comparisons to the estimate are presented in this paper. This study illustrates the gap between linear components of anthropometry and the need for overall volume metrics in order to provide solutions. A second case study examines the overlay of the space suit scans and components onto scanned individuals to quantify fit and clearance to aid in sizing the suit to the individual. Restrictions in space suit size availability present unique challenges to optimally fit the individual within a limited sizing range while maintaining performance. Quantification of the clearance and fit between similarly sized individuals is critical in providing a greater understanding of the human body's function within the suit. The third case study presented in this paper explores the development of a conformal seat pan using scanning techniques, and details the challenges of volumetric analyses that were overcome in order to develop a universal seat pan that can be utilized across the entire user population. The final case study explores expanding volumetric capabilities through generation of boundary manikins. Boundary manikins are representative individuals from the population of interest that represent the extremes of the population spectrum. The ABF developed a technique to take three-dimensional scans of individuals and manipulate the scans to reflect the boundary manikins' anthropometry. In essence, this process generates a representative three-dimensional scan of an individual from anthropometry, using another individual's scanned image. The results from this process can be used in design process modeling and initial suit sizing work as a three dimensional, realistic example of individuals from the population, maintaining the variability between and correlation to the relevant dimensions of interest.
Generation of Boundary Manikin Anthropometry
The purpose of this study was to develop 3D digital boundary manikins that are representative of the anthropometry of a unique population. These digital manikins can be used by designers to verify and validate that the components of the spacesuit design satisfy the requirements specified in the Human Systems Integration Requirements (HSIR) document. Currently, the HSIR requires the suit to accommodate the 1st percentile American female to the 99th percentile American male. The manikin anthropometry was derived using two methods: Principal Component Analysis (PCA) and Whole Body Posture Based Analysis (WBPBA). PCA is a statistical method for reducing a multidimensional data set by using eigenvectors and eigenvalues. The goal is to create a reduced data set that encapsulates the majority of the variation in the population. WBPBA is a multivariate analytical approach that was developed by the Anthropometry and Biomechanics Facility (ABF) to identify the extremes of the population for a given body posture. WBPBA is a simulation-based method that finds extremes in a population based on anthropometry and posture whereas PCA is based solely on anthropometry. Both methods yield a list of subjects and their anthropometry from the target population; PCA resulted in 20 female and 22 male subjects anthropometry and WBPBA resulted in 7 subjects' anthropometry representing the extreme subjects in the target population. The subjects anthropometry is then used to 'morph' a baseline digital scan of a person with the same body type to create a 3D digital model that can be used as a tool for designers, the details of which will be discussed in subsequent papers.