Matthew B. Parkinson

The objective of this work is to improve Universal Design opportunities through a better understanding of data on body size and shape from global populations. Products and environments that physically interact with users are often designed using anthropometric data that are either detailed but demographically narrow, or representative of a target population but missing the measures necessary for design. This mismatch constrains designers’ ability to properly consider human variability and can lead to inequitable outcomes when designs are shared across more diverse or global populations. Universal Design calls for products, environments, and systems that are usable by the widest range of people, yet these goals are difficult to operationalize when available data do not reflect the intended users. This paper considers data on body size and shape from seven populations around the world: Chile, Egypt, Kenya, Germany, India, Japan, and the United States. A common set of anthropometric measures relevant to design was reconstructed for each dataset using data synthesis methods and then analysed using principal component analysis to characterize the dominant patterns of anthropometric variation. The results show that relying on data from a single country can compromise equitable fit, safety, comfort, and performance. This underscores the value of multivariate, population-informed approaches to Universal Design.

This study examines how seat width, load factor, and demographics influence passenger ratings of sufficiency, acceptability, and comfort in aircraft seating. Data from a subjective seating study relates seated hip breadth and seat width to these passenger outcomes. A parametric study and Virtual Fit Trials combined anthropometric data with empirical spatial comfort models to simulate the effects of varying seat widths, load factors, and passenger demographics. This extends earlier work based only on anthropometric fit by incorporating subjective preference for space. Results show that wider seats substantially improve accommodation across all metrics, while higher load factors reduce comfort by limiting adjacent empty seats. Female passengers were disproportionately disaccommodated across all metrics due to larger seated hip breadths. A case study comparing 3:3 and wider 3:2 seating in a fixed-width fuselage showed improved accommodation but reduced capacity, highlighting the trade-off between passenger comfort and airline efficiency.

The objective of this work is to identify the most effective techniques for reweighting anthropometric data such that it accurately represents a target user population. Seven methods are compared, including uniform weighting, stratification and permutations of nearest neighbour (NN) reweighting. The analysis illuminates the performance of existing and novel approaches to reweighting data specifically for approximating body size and shape (‘anthropometry’). While uniform weighting and stratified sampling are often used in this field, the present analysis indicates that lower-order NN approaches will produce more representative results. Although anthropometric data are crucial to the design of artefacts, tasks and environments, finding appropriate representative data is challenging. Designers and ergonomists are unlikely to find data that are simultaneously accessible, up-to-date, detailed and from the relevant population. The application of new statistical weights – reweighting – is one useful strategy for meeting this shortfall. This research indicates the best methods for reweighting and provides guidance for sampling strategies in future data collection efforts. Practitioner Summary: Reweighting anthropometric data is one strategy for matching available data to a target user population. Stratified sampling is often used as the method for calculating weights, but it has been shown to produce inaccurate estimates. This research examines seven strategies and finds low-order NN approaches are the more accurate methods.

The purpose of this work is to investigate the relationship between the disciplinary diversity of capstone design teams and perceptions of success and engineering design abilities. Capstone design programs are effective environments for students to collaborate with industry sponsors on authentic design problems. They provide students with the opportunity to hone their technical and

When designing products and environments, detailed data on body size and shape are seldom available for the specific user population. One way to mitigate this issue is to reweight available data such that they provide an accurate estimate of the target population of interest. This is done by assigning a statistical weight to each individual in the reference data, increasing or decreasing their influence on statistical models of the whole. This paper presents a new approach to reweighting these data. Instead of stratified sampling, the proposed method uses a clustering algorithm to identify relationships between the detailed and reference populations using their height, mass, and body mass index (BMI). The newly weighted data are shown to provide more accurate estimates than traditional approaches. The improved accuracy that accompanies this method provides designers with an alternative to data synthesis techniques as they seek appropriate data to guide their design practice.Practitioner Summary: Design practice is best guided by data on body size and shape that accurately represents the target user population. This research presents an alternative to data synthesis (e.g. regression or proportionality constants) for adapting data from one population for use in modelling another.

The objective of this work is to introduce a new method for determining preliminary design specifications related to human-artifact interaction. This new method uses data mining of large numbers of consumer reviews. User opinion on specific product features can be time-consuming or expensive to obtain through traditional methods including surveys, experiments, and observational studies. Data mining review text of already released products may be a potentially less time consuming and costly method. Previously established methods of determining design for human variability information from consumer reviews, such as the frequency and accuracy summation (FAS) number and subsequent manual analysis, are explored. The weighted phrase rating (WPR), a new metric which can be an automated tool to quickly analyze consumer reviews, is also introduced. It does not require manual parsing of the reviews, which extends its applicability to larger review pools. This new method is shown to quickly and economically provide information useful to the establishment of design specifications.

The objective of this research is to model the geometric variability of the glenoid of the scapula. The glenoid is the “socket” component of the “ball and socket” connection of the shoulder joint. The model must capture the observed variability with sufficient resolution such that it informs both operative and design decisions. Creating the model required the application of existing mathematical and statistical modeling approaches, including geometric fitting, radial basis functions (RBFs), and principal component analysis (PCA). The landmark identification process represented the glenoid in a new manner. This work was validated against existing approaches and computed tomography (CT) scans from 42 patients. Information on the range of shoulder geometries can assist with preoperative planning as well as implant design for total shoulder arthroplasty (TSA). PCA was used to quantify the variability of shape across landmarks used to represent the glenoid shape. These landmark locations could be used to generate full surface meshes of existing glenoids or new glenoid models synthesized by changing principal components (PC). The process of creation of these shoulder geometries may be useful for the study of other joints. The models created will help surgeons and engineers to understand the effects of osteoarthritis on bone geometry, as well as the range of variability present in healthy shoulders.

The objective of this work is to demonstrate a method for examining the competing effects of secular trends in body size, seat size and configuration, and the increased load factor of airplanes. The method uses statistical modeling and virtual fit testing to provide a flexible environment for exploring the impact of various parameters on passenger accommodation. A case study demonstrates the method by exploring the effect of seat width on the accommodation of US civilians (based on seated hip breadth). The case study demonstrates that recent trends of decreasing seat widths and increasing load factors lead to higher disaccommodation. Based on anthropometry and virtual fit, women are also shown to be disproportionately disaccommodated compared to men. Practitioner Summary: Airlines are reducing seat width at the same time that individuals worldwide are getting larger. Flights are increasingly crowded, with load factor at a record high. This paper explores the effects of seat width on passenger accommodation under several scenarios involving load factor, demographics, and passenger seating allocation strategies.

The objective of this research is to model the geometric variability of the glenoid (the “socket” component of the “ball and socket” connection of the shoulder joint) of the scapula. The model must capture the observed variability with sufficient resolution such that it informs operative and design decisions. This required the quantification of variability in landmark locations and relevant bone geometry. Landmarks were placed on the existing glenoid meshes, such that they provided enough information to represent the geometry, while being consistent across each glenoid. Additionally, the surface geometry of the glenoid vault was modeled. This required the application of existing mathematical and statistical modeling approaches, including geometric fitting, radial basis functions, and principal component analysis. The landmark identification process represented the glenoid in new manner. The work was validated against existing approaches and CT scans from 42 patients. A range of information on shoulder geometries can assist with preoperative planning, as well as implant design, for Total Shoulder Arthroplasty (TSA). Principal component analysis (PCA) was used to quantify the variability of shape across the glenoid landmarks, and synthesize new glenoid models. The process of creation of these shoulder geometries may possibly be useful for the study of other joints. The models created will help surgeons and engineers to understand the effects of osteoarthritis on bone geometry, as well as the range of variability present in healthy shoulders.