Christopher J. Garneau

A comparison of methodologies for designing for human variability

In the design of artefacts that interact with people, the spatial dimensions of the user population are often used to size and engineer the artefact. The variability in anthropometry indicates the fixed allocation of space, adjustability requirements, or how many sizes are needed to accommodate the intended user population. Various tools are used to achieve this goal, including boundary manikins, digital human models, prototypes and population models, and hybrid methods that combine the approaches. The present work explores each of these and their relative strengths and weaknesses. This is done in the context of a univariate case study involving the adjustability requirements of a stationary bicycle. An experiment involving 51 individuals was conducted to obtain the data necessary for utilising and evaluating the methods.

Optimization of Tool Handle Shape for a Target User Population

One goal of Designing for Human Variability (DfHV) is to optimize the interaction between user and device. Often, this interaction is dictated by the spatial dimensions or shape of the artifacts with which people interact. A novel approach that applies DfHV principles including virtual fitting trials to optimize the shape of an artifact is presented and applied to the design of a tool handle. By breaking the problem apart into discrete blocks, called the hand model and tool model, application of standard optimization techniques is facilitated. The benefits of the approach include the ability to consider handles with variable cross-sections and to systematically consider the effects of multiple sizes. The methodology presented here is configurable for any given population and may be applied to other DfHV design problems.Copyright

Studying Analysts’ Data Triage Operations in Cyber Defense Situational Analysis

Cyber defense analysts are playing a critical role in Security Operations Centers (SOCs) to make sense of the immense amount of network monitoring data for detecting and responding to cyber attacks, including large-scale cyber attack campaigns involving advanced persistent threats. The network data continuously generated by multiple cyber defense systems, which may contain many false alerts, are overwhelming to the analysts. Analysts often need to make quick decisions/responses in a very short time based on their awareness of the situation at that moment. Data triage is the first and the most fundamental step performed routinely by the analysts — it filters a massive network monitoring data to identify known malicious events. Due to the high noise-to-signal ratio of network monitoring data, this steps accounts for a very significant portion of the time and attention of intrusion detection analysts. Therefore, a smart human-machine system that improves the performance of data triage operation in SOC is highly desirable. In this chapter, we describe a human-centered smart data triage system that leverages the cognitive trace of intrusion detection analysts. Our approach is based on a dynamic cyber-human system that integrates three dimensions: cyber defense analysts, network monitoring data, and attack activities. The approach leverages recorded analytic processes of intrusion detection analysts, which we refer to as “cognitive traces”. These traces of the analysts capture the examples of malicious events detected from the network monitoring data. Such traces from senior analysts provide a powerful opportunity for training junior analysts in performing data triage operations. To realize this potential, we also developed a smart retrieval framework that automatically retrieves traces of other senior analysts based on their similarity to the events already identified by a junior analyst. The traces from analysts, as demonstrated by a case study, also enable us to better understand their analytic processes in a systematic, yet minimum-reactive way. We summarize this chapter by discussing limitations of the proposed framework and the directions of future research regarding improving the data triage operations of cyber defense analysts.

A survey of anthropometry and physical accommodation in ergonomics curricula

The size and shape of users are an important consideration for many products and environments. Designers and engineers in many disciplines must often accommodate these attributes to meet objectives such as fit and safety. When practitioners have academic training in addressing these issues, it is typically through courses in Human Factors/Ergonomics (HF/E). This paper investigates education related to physical accommodation and offers suggestions for improvement. A survey was conducted wherein 21 instructors at 18 universities in the United States provided syllabi for 29 courses, which were analysed to determine topics related to anthropometry and resources used for the courses. The results show that within the US, anthropometry is covered in the majority of courses discussing physical ergonomics, but important related concepts were often omitted (e.g. digital human modelling, multivariate accommodation and variability across global populations). Curricula could be improved by incorporating more accurate anthropometry, multivariate problems and interactive online tools. Practitioner Summary: This paper describes a study investigating collegiate ergonomics courses within the US in the area of physical accommodation. Course schedules and texts were studied for their treatment of several topics related to accommodating the spatial requirements (anthropometry) of users. Recommendations are made for improving course curricula.

Considering just noticeable difference in assessments of physical accommodation for product design

Configuring products or environments for the size of their human users requires the consideration of several characteristics of the target user population, including body dimensions (anthropometry) and preferred interaction. Users are both adaptable and imperfect observers, which often makes it difficult for them to distinguish between candidate designs. This insensitivity is described by a concept called ‘just noticeable difference’, or JND. This paper presents an implementation of JND modelling and demonstrates how its use in the sizing of products or environments for target user populations can improve expected performance. Two facets of this problem are explored: (1) how experimental measures of JND for dimensional optimisation tasks may be obtained, and (2) how measures of JND may be included in models of user–device interaction for both adjustable and discretely sized products and the assumptions required. A case study demonstrating the collection and modelling of JND for a simple univariate problem is also presented. Practitioner Summary: Since people are adaptable and imperfect observers, there exists a ‘just noticeable difference’ that can be considered when designing products and environments. When JND is modelled for a target population, less variability in design dimensions due to physical user requirements may be necessary. This paper considers JND in quantitative simulations of population accommodation.

Visual Analysis of User Accommodation

This study presents a novel, quantitative tool for design decision-making for products designed for human variability. Accommodation, which describes the ability of a user to interact with a device or environment in a preferred way, is a key product performance metric. Methods that offer a better understanding of accommodation of broad user populations would allow for the design of products that are more cost-effective, safer, and/or lead to greater levels of customer satisfaction. Target user populations are often characterized by measures of anthropometry, or body dimensions. A methodology is proposed that uses a visual analysis method for understanding and exploring accommodation across the variability in anthropometry of a target user population. This is achieved by assessing binary accommodation of individuals using a “virtual fit” method and examining trends in binary accommodation across the range of anthropometric variability, referred to as the “anthropometry space”. Various factors influencing accommodation, such as user preference independent of anthropometry and the quality of a design, are also discussed and are an important contribution of the work. Two demonstration studies are presented that illustrate the methodology and provide opportunity for discussion of its impact. The first study investigates the simple univariate problem of dimensionally optimizing the seat height and range of adjustability of an exercise cycle. The second study investigates the more complex problem of optimally configuring the driver package of a commercial truck.Copyright

Considering Secular and Demographic Trends in Designing for Present and Future Populations

In products designed for human variability, the anthropometry (body measurements) of the target user population constitutes a primary source of variability that must be considered in the optimization of the spatial dimensions of the product. Accommodation, which describes the ability of a user to interact with a device or environment in their preferred manner, is a key measure of its performance. Other studies have considered various methods for accounting for the variability in anthropometry in a target user population to calculate estimated accommodation, but few have explicitly considered the effects of secular trends and demographic changes over time. This paper considers these changes in the context of a case study involving truck drivers and cab geometry. The truck driver populations are used to illustrate changes in body size and shape over a 30-year period and show how they affect user acceptability of designs. Changes in the gender split of the driver population are also considered, and are shown to have a significant effect on accommodation. The work demonstrates that secular trends and demographic changes over time significantly affect accommodation, but a well designed product will be more robust to these changes.Copyright

Simultaneous consideration of user acceptability and regulatory compliance in vehicle seat design

The success of a vehicle seat is defined in large part by its acceptability to users and compliance with applicable regulations. Simultaneously satisfying both of these objectives can be challenging, and it is the goal of the designer to balance the requirements of each to optimise the design. Quantifying the many sources of variability, including that which results from human users and manufacturers, is necessary for achieving satisfactory and predictable results. Here, the relationship between meeting FMVSS 202a, a new regulation related to head restraints in the USA, and achieving user acceptability is explored as an example of a vehicle seat design scenario presenting conflicting objectives. Sources of variability in this problem are identified as originating from test manikin installers, customers, and manufacturers. The impact of variability resulting from these sources on simultaneously achieving the stated objectives is investigated.

Use of the Augmented REality Sandtable (ARES) to Enhance Army CBRN Training

This paper presents the results of an evaluation of the Augmented REality Sandtable (ARES) as a training tool during the Chemical, Biological, Radiological, and Nuclear (CBRN) Captain’s Career Course (C3) Table Top Exercise (TTX). Two teams, one that used ARES and one that did not, were compared across a series of course assessments, knowledge acquisition tests, and self-reported questionnaires. The ARES team used the system to develop various map overlays, evaluate their proposed strategies while integrating feedback from the CBRN plume-transport and dispersion simulations, and brief their results to the course instructor for evaluation. Results reveal an overall positive perception of ARES in terms of supporting the development of course outputs. Recommendations for future iterations of the system were gathered from the ARES team following the TTX.

Me and My VE, Part 5: Applications in Human Factors Research and Practice

Recent advances in technology have made virtual environments, virtual reality, augmented reality, and simulations more affordable and accessible to researchers, companies, and the general public, which has led to many novel use cases and applications. A key objective of human factors research and practice is determining how these technology-rich applications can be designed and applied to improve human performance across a variety of contexts. This session will demonstrate some of the distinct and diverse uses of virtual environments and mixed reality environments in an alternative format. The session will begin with each demonstrator providing a brief overview of their virtual environment (VE) and a description of how it has been used to address a particular problem or research need. Following the description portion of the session, each VE will be set-up at a demonstration station in the room, and session attendees will be encouraged to directly interact with the virtual environment and ask demonstrators questions about their research and inquire about the effectiveness of using VE for research, training, and evaluation purposes. The overall objective of this alternative session is to increase the awareness of how human factors professionals use VE technologies and increase the awareness of the capabilities and limitations of VE in supporting the work of HF professionals.