scholarly journals Virtual Modeling of User Populations and Formative Design Parameters

Systems ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 35
Author(s):  
Benjamin M. Knisely ◽  
Monifa Vaughn-Cooke
Keyword(s):  
Performance Studies ◽  
Human Performance ◽  
Target Population ◽  
Population Heterogeneity ◽  
Design Parameters ◽  
Formative Design ◽  
Virtual Population ◽  
Digital Human Models ◽  
Virtual Modeling ◽  
Digital Human

Human variability related to physical, cognitive, socio-demographic, and other factors can contribute to large differences in human performance. Quantifying population heterogeneity can be useful for designers wishing to evaluate design parameters such that a system design is robust to this variability. Comprehensively integrating human variability in the design process poses many challenges, such as limited access to a statistically representative population and limited data collection resources. This paper discusses two virtual population modeling approaches intended to be performed prior to in-person design validation studies to minimize these challenges by: (1) targeting recruitment of representative population strata and (2) reducing the candidate design parameters being validated in the target population. The first approach suggests the use of digital human models, virtual representations of humans that can simulate system interaction to eliminate candidate design parameters. The second approach suggests the use of existing human databases to identify relevant human characteristics for representative recruitment strata in subsequent studies. Two case studies are presented to demonstrate each approach, and the benefits and limitations of each are discussed. This paper demonstrates the benefit of modeling prior to conducting in-person human performance studies to minimize resource burden, which has significant implications on early design stages.

Consideration of Demographics and Variance in Regression Approaches to Estimating Body Dimensions for Spatial Analysis of Design

2010 ◽  
Vol 132 (2) ◽  
Author(s):  
Gopal Nadadur ◽  
Matthew B. Parkinson
Keyword(s):  
Regression Model ◽  
Target Population ◽  
Residual Variance ◽  
Use Of Data ◽  
Target User ◽  
Digital Human Models ◽  
And Performance ◽  
Marginal Improvement ◽  
The Military ◽  
Digital Human

A common objective in designing for human variability is to consider the variability in body size and shape of the target user population. Since anthropometric data specific to the user population of interest are seldom available, the variability is approximated. This is done in a number of ways, including the use of data from populations that are well-documented (e.g., the military), proportionality constants, and digital human models. These approaches have specific limitations, including a failure to consider the effects of lifestyle and demography, resulting in products, tasks, and environments that are inappropriately sized for the actual user population, causing problems with safety, fit, and performance. This paper explores a regression-based approach in a context where the demographic distributions of descriptors (e.g., race/ethnicity, age, and fitness) are dissimilar for the database and target population. Also examined is a stratified regression model involving the development of independent anthropometry-estimation models for each racial group. When using regression with residual variance, stratification on the predictor demographics to obtain estimates of gender, stature, and BMI distributions is shown to be sufficiently robust for usual database-target population combinations. Consideration of demographic variables in development of the regression model provides marginal improvement, but could be appropriate in specific situations.

Using Multivariate Analysis to Select Accommodation Boundary Manikins From a Population Database

2015 ◽  
Author(s):  
Devon K. Boyd ◽  
Matthew B. Parkinson
Keyword(s):  
Principal Component Analysis ◽  
Multivariate Analysis ◽  
Principal Component ◽  
Target Population ◽  
Component Analysis ◽  
Pareto Optimization ◽  
Population Database ◽  
Human Models ◽  
Digital Human Models ◽  
Digital Human

Digital Human Models (DHMs) are a tool that can be used to aid in determining dimensions for human-centered designs. DHMs have the ability to represent the anthropometric extremes of the population and help to determine which dimensions should be used to acquire a certain level of accommodation within a population. It is not possible to use current techniques for selecting manikins that represent a population, like principal component analysis (PCA), the application of design families, or percentiles due to these methods having a lower output accommodation levels than expected. The purpose of this research is to provide a multivariate analysis based on Pareto optimization. This method determines a pool of manikins representing the total target population when comparing up to three anthropometric dimensions within a database. This pool will act as boundary manikins for a given level of accommodation.

scholarly journals Digital Human Models for Human-Centered Design

2017 ◽  
Vol 29 (5) ◽  
pp. 783-789 ◽  
Author(s):  
Masaaki Mochimaru ◽  
Keyword(s):  
Computer Aided Design ◽  
Target Population ◽  
Virtual Space ◽  
Support Design ◽  
Human Centered Design ◽  
Human Models ◽  
Digital Human Models ◽  
Body Shapes ◽  
Aided Design ◽  
Digital Human

Digital human models represent variations of body shapes for the target end-user population. They can simulate human motions, evaluate workloads, and are utilized to assess safety and usability of products and environments in a virtual space with computer-aided design. The digitalized process can reduce actual test panels, time and cost for human-centered design. Recent trends in research show that the target population of digital human models includes people with special needs. Moreover, digital human models are embedded into interactive tools to support design workshop.

Accessible Sleeper for the Next Generation Passenger Rail Vehicles

2018 ◽  
Author(s):  
Kamolnat Tabattanon ◽  
Kate Hunter-Zaworski
Keyword(s):  
Design Process ◽  
Computer Aided Design ◽  
Online Survey ◽  
Target Population ◽  
Full Scale ◽  
Passenger Rail ◽  
Conceptual Design Phase ◽  
Rail Industry ◽  
Digital Human Models ◽  
Digital Human

This Safety IDEA project-31 extends the design process for the accessible sleeper compartments to include 3-D digital modeling and anthropometric analyses and uses a full-scale soft mock-up of the sleeper compartment. The use of computer-aided design tools permits human factors constraints, including minimum spatial requirements and reach limitations, to be determined within the conceptual design phase without physical prototyping and data collection. In this ongoing study, physical prototyping in the form of a full-scale soft mock-up is used to validate digital results. Successful validation would indicate that anthropometric digital human models based on regular anthropometric databases may be used to design for populations with reduced mobility, provided that the wheeled mobility devices are modelled appropriately and advance the design process for accessible spaces. The soft mock-up permits spatial evaluation by the general public including people with disabilities. An online survey is also available to gather feedback and the needs and values of the target population. Representatives of the passenger rail industry are involved throughout the project and have been invited to participate in the evaluation of the soft mock up. The results of the project are validated designs for new accessible sleeper compartments for bi-level and single-level rail cars and include seating, sleeping, and restroom spaces. This will be disseminated for use by the passenger rail industry.

Advancing Design Through the Creation and Visualization of Virtual Population Representing U.S. Civilians

2014 ◽  
Author(s):  
D. Reuben Haupt ◽  
Matthew B. Parkinson
Keyword(s):  
Body Size ◽  
Waist Circumference ◽  
Regression Models ◽  
Model Parameters ◽  
Civilian Population ◽  
Size And Shape ◽  
Virtual Population ◽  
Digital Human Models ◽  
Digital Human ◽  
The U.S

Visualization of the U.S. civilian population provides perspective on the variability of body size and shape, enabling designers and engineers to better understand the needs of their target users. This paper presents a virtual population of digital human models, representative of the U.S. civilian population, and the methods used to create it. It is based on the observed variability in stature, BMI, and waist circumference in the data from the 2007–2010 CDC NHANES survey. The NHANES data were used in conjunction with regression models to develop the required model parameters. The models were then presented such that the variability and distribution of variability in anthropometry can be easily seen.

Digital Human Modeling for Workspace Design

2008 ◽  
Vol 4 (1) ◽  
pp. 41-74 ◽  
Author(s):  
Don B. Chaffin
Keyword(s):  
Computer Aided Design ◽  
Human Performance ◽  
Digital Human Modeling ◽  
Cad Systems ◽  
Work Settings ◽  
Biomechanical Models ◽  
Human Modeling ◽  
Digital Human Models ◽  
Manual Tasks ◽  
Digital Human

Digital human modeling (DHM) technology offers human factors/ergonomics specialists the promise of an efficient means to simulate a large variety of ergonomics issues early in the design of products and manufacturing workstations. It rests on the premise that most products and manufacturing work settings are specified and designed by using sophisticated computer-aided design (CAD) systems. By integrating a computer-rendered avatar (or hominoid) and the CAD-rendered graphics of a prospective workspace, one can simulate issues regarding who can fit, reach, see, manipulate, and so on. In this chapter, I briefly describe the development of various DHM methods to improve CAD systems. Past concerns about early DHM methods are discussed, followed by a description of some of the recent major developments that represent attempts by various groups to address the early concerns. In this latter context, methods are described for using anthropometric databases to ensure that population shape and size are well modeled. Efforts to integrate various biomechanical models into DHM systems also are described, followed by a section that outlines how human motions are being modeled in different DHM systems. In a final section, I discuss recent work to merge cognitive models of human performance with DHM models of manual tasks. Much has been accomplished in recent years to make digital human models more useful and effective in resolving ergonomics issues during the design of products and manufacturing processes, but much remains to be learned and applied in this rapidly evolving aspect of ergonomics.

Experimental Study of an Airplane Accident Evacuation/Rescue Simulation Using 3D Kinematic Digital Human Models

2014 ◽  
Author(s):  
Takao Kakizaki ◽  
Jiro Urii ◽  
Mitsuru Endo
Keyword(s):  
Test Field ◽  
Evacuation Simulation ◽  
Evacuation Time ◽  
Digital Human Models ◽  
Emergency Exit ◽  
Simulation Results ◽  
Evacuation Drills ◽  
Walking Speeds ◽  
Mass Evacuation ◽  
Digital Human

The 3D mass evacuation simulation of an airplane accident is experimentally verified. Evacuee motion has been experimentally investigated by building a test field that emulates the interior of an actual regional airliner with a capacity of approximately 100 passengers. The experiment results indicate that the evacuation time tends to be affected by the number of passengers and the evacuee guidance at the emergency exit. The results also indicate that any evacuation delay in exiting by individual passengers only slightly affects the total evacuation time because of evacuee congestion in the aisles. Moreover, the importance of evacuation guidance notification was investigated based on the evacuation-order variance. Finally, the experimental results were compared to the corresponding simulation results. Simulations using appropriate evacuee walking speeds can provide valid evacuation times, which are the most important factor in designing evacuation drills. Consequently, these results should be applied to existing 3D simulations using precise KDH models for more accurate mass evacuation/rescue simulations.

Exploring the Design Space Using a Surrogate Model Approach With Digital Human Modeling Simulations

2018 ◽  
Author(s):  
Salman Ahmed ◽  
Mihir Sunil Gawand ◽  
Lukman Irshad ◽  
H. Onan Demirel
Keyword(s):  
Human Factors ◽  
Surrogate Model ◽  
Human Performance ◽  
Design Method ◽  
Human Subjects ◽  
Design Stage ◽  
Digital Human Modeling ◽  
Design Variables ◽  
Human Modeling ◽  
Digital Human

Computational human factors tools are often not fully-integrated during the early phases of product design. Often, conventional ergonomic practices require physical prototypes and human subjects which are costly in terms of finances and time. Ergonomics evaluations executed on physical prototypes has the limitations of increasing the overall rework as more iterations are required to incorporate design changes related to human factors that are found later in the design stage, which affects the overall cost of product development. This paper proposes a design methodology based on Digital Human Modeling (DHM) approach to inform designers about the ergonomics adequacies of products during early stages of design process. This proactive ergonomics approach has the potential to allow designers to identify significant design variables that affect the human performance before full-scale prototypes are built. The design method utilizes a surrogate model that represents human product interaction. Optimizing the surrogate model provides design concepts to optimize human performance. The efficacy of the proposed design method is demonstrated by a cockpit design study.

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