A Design Framework to Automate Task Simulation and Ergonomic Analysis in Digital Human Modeling

Gawand, Mihir Sunil; Demirel, Hasan

doi:10.1007/978-3-030-49904-4_4

Cited by 5 publications

(1 citation statement)

References 15 publications

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“…When using DHMs to evaluate design parameters and the interaction is static or relatively simple, it is suggested some amount of automation be used to expedite model throughput. Past work has demonstrated this to be a viable option [68]. Based on the results from Case Study 1, it is believed these simulations can be reliably and consistently automated.…”

Section: Dhm Applications and Limitationsmentioning

confidence: 97%

Virtual Modeling of User Populations and Formative Design Parameters

Knisely

Vaughn-Cooke

2020

Systems

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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.

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Section: Dhm Applications and Limitationsmentioning

confidence: 97%