Engineering:Digital Human Modeling (DHM)

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Short description: A field encompassing computer-based techniques and methodologies that simulate human characteristics


Digital human modeling (DHM) technology refers to the creation of digital representations of individuals that encompass their size, proportions, musculature, and movement characteristics. This technology allows for the integration of virtual humans into computer-aided design (CAD) systems and virtual reality (VR) environments. DHM software utilizes advanced visualization techniques combined with mathematical and scientific principles to assist designers in assessing the safety and efficacy of their designs.

By employing DHM, designers can generate digital models that represent diverse populations, enabling them to evaluate various design alternatives in a virtual context. This approach facilitates virtual testing, which can significantly decrease the time and costs associated with modifications to physical prototypes during the later stages of the design process. This efficiency contributes to improved design outcomes and enhances user-centered design practices.[1]

Definition

Digital human modeling (DHM) encompasses a diverse range of methodologies and technologies designed to represent human characteristics and behaviors within digital or virtual environments. The interpretation of DHM can vary considerably across different disciplines and fields, leading to a multitude of applications.

In ergonomics, DHM is an essential tool for Human Factors and Ergonomics (HFE) specialists, allowing them to simulate and analyze ergonomic factors that are critical to product design and workplace environments. From a design perspective, DHM integrates human body dimensions, postures, and behaviors into computer-aided design (CAD) systems, thereby enhancing product usability and user comfort.

Moreover, DHM extends into behavioral sciences by modeling cognitive processes and decision-making. This interdisciplinary approach demonstrates the versatility of DHM across various sectors, including manufacturing, healthcare, and virtual reality. In these domains, DHM plays a crucial role in optimizing human-system interactions and evaluating the feasibility of designs.

A broader definition of DHM is:

"A research domain that focuses on synthesizing and applying theory, principles, methods, and technology from a wide range of disciplines. This domain enables computational visualization, modeling, and simulation of human-systems interactions. The goal is to facilitate the prediction and optimization of human well-being and performance".[1]

Benefits and Challenges of Designing with Digital Human Models (DHM)

Digital human modeling (DHM) provides several notable advantages within the design process. One of the primary benefits is its cost-effectiveness; DHM can significantly reduce overall design costs by enabling early ergonomic assessments and minimizing the need for physical prototypes.

Additionally, DHM tools equip designers—regardless of their level of expertise in ergonomics—to perform fundamental ergonomic evaluations. These tools encompass a variety of features, including:

  1. 3D Human Models: These models accurately represent physical attributes, allowing for realistic simulations.
  2. Vision Analysis Tools: Designed to assess peripheral coverage and identify obscuration zones.
  3. Predefined Postures: Predictive models generate realistic poses for various scenarios.
  4. Comfort and Injury Risk Assessment Toolkits: These toolkits facilitate the evaluation of comfort levels and potential injury risks associated with designs.
  5. Performance Measurement Tools: These tools calculate important factors such as comfort, fatigue, energy expenditure, static strength, and cognitive load, although some limitations may apply.[1]

Despite its advantages, Digital Human Modeling (DHM) presents several notable challenges. One significant issue is the fidelity limitations of DHM simulations, which may fail to accurately reflect real-world variations in user posture and behavior. This discrepancy can result in misleading or inaccurate outcomes during the design process.[1]

Another challenge is the representativeness of manikins within DHM libraries. These libraries may lack comprehensive data for all user populations, including underrepresented groups such as the elderly and individuals with disabilities. This limitation can hinder the applicability of DHM in creating inclusive designs that address the needs of diverse user groups.[1]

The integration of Digital Human Modeling (DHM) with Computer-Aided Engineering (CAE) systems is often insufficient, resulting in cumbersome workflows for designers. Integrated DHM-CAE systems, such as the Catia manikin, facilitate rapid ergonomic assessments directly within the design platform. This capability eliminates the need for frequent file conversions and transfers, thereby streamlining the design process.[2]

In contrast, standalone DHM software typically necessitates ongoing file transfers between DHM and CAE programs for design modifications. This approach can be time-consuming and disrupt the overall design flow, leading to inefficiencies in the development process.[2]

Many Digital Human Modeling (DHM) tools primarily concentrate on physical ergonomics, often overlooking cognitive and perceptual factors such as human emotion, decision-making, and mental workload. To achieve a comprehensive ergonomic analysis, an ideal DHM platform should integrate both physical and cognitive data. This integration would enable the incorporation of cognitive models, including elements like facial expressions, stress levels, and mental workload, thus providing a more holistic understanding of user interactions and experiences.[3]

Applications of DHM

Applications in the Automobile Industry

Digital Human Modeling (DHM) plays a significant role in the automobile industry by enhancing vehicle design and safety. It is instrumental in optimizing vehicle packaging through the analysis of interior space allocation, which improves both comfort and functionality. DHM evaluates driving comfort by considering human body dimensions (anthropometry) to ensure that controls and displays are appropriately positioned for drivers of varying sizes. Additionally, visual analysis using DHM assesses the visibility of essential controls behind the steering wheel, identifying potential obstructions from pillars or other interior elements that could impair driver visibility.[1]

Applications in the Aviation and Space Industries

In the aviation and space sectors, DHM is integral to the design, manufacturing, and maintenance processes for civil (e.g., Boeing 777), military (e.g., F-15, F-22), and space vehicles (e.g., ISS MPLM). DHM plays a crucial role in ergonomic design by identifying and addressing ergonomic issues early in the development phase, ensuring that personnel of various body sizes can safely and comfortably perform their tasks. This proactive approach not only reduces costs associated with physical prototyping and human testing—particularly in microgravity environments like space stations—but also enhances safety by mitigating risks during maintenance and operations.[1]

Applications in Production (Assembly and Manufacturing)

DHM is critical in ergonomic assessment and design across various industries, focusing on safety, comfort, and efficiency in workplace environments. Utilizing methodologies such as the Rapid Upper Limb Assessment (RULA) and the Ovako Working Posture Analysis System (OWAS), DHM analyzes safety and potential injury risks during the design phase of workstations and tasks. Simulations conducted by DHM assess joint angles and comfort levels for workers of diverse anthropometry, ensuring ergonomic suitability across different body sizes.[1]

Applications in Medicine and Healthcare

In medicine, key applications of DHM include the ergonomic assessment of medical products, where usability and user interaction with devices are evaluated across a spectrum of abilities. DHM also aids in accessibility design, providing insights into how individuals with disabilities interact with medical equipment, such as wheelchairs and walkers. In rehabilitation planning, DHM simulations offer valuable tools for assessing potential outcomes of procedures or therapeutic interventions before implementation. Moreover, voxel-based DHM contributes detailed anatomical models for advanced medical mannequins used in training, medical illustrations, and prosthetic development.

Future advancements in DHM within medicine may involve integrating DHM with advanced visualization technologies such as 3D tomography, virtual reality (VR), augmented reality (AR), and haptic feedback systems. These integrations aim to enhance surgical planning and simulations, improving precision and outcomes. Additionally, DHM combined with haptic interfaces holds promise for advancing medical education and training, particularly in developing palpation skills and enhancing tactile feedback for learners.[1]

Applications in Consumer Goods

DHM facilitates comprehensive ergonomic evaluations throughout product development, catering to diverse user groups and identifying potential accessibility issues, repetitive strain risks, and awkward postures during maintenance tasks. It optimizes ergonomic design by simulating interactions with customers, manufacturing workers, and maintenance personnel, thereby enhancing comfort and usability. Emerging trends in DHM include product personalization through 3D scanning and anthropometric data, enabling the development of customized products, such as scoliosis braces.[1]

DHM Software Tools

  1. Siemens Jack  [4]
  2. RAMSIS [5]
  3. Santos Pro[6]
  4. 3DSSPP[7]
  5. HumanCAD 4[8]
  6. AnyBody Modeling[9]
  7. MADYMO[10]
  8. DELMIA Human[11]
  9. IPS IMMA[12]

References

  1. ↑ 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 H. Onan Demirel, Salman Ahmed, and Vincent G. Duffy (2022). "Digital Human Modeling: A Review and Reappraisal of Origins, Present, and Expected Future Methods for Representing Humans Computationally". International Journal of Human-Computer Interaction 38 (10): 897–937. doi:10.1080/10447318.2021.1976507. 
  2. ↑ 2.0 2.1 Badler, N. I., Allbeck, J., Lee, S.-J., Rabbitz, R. J., Broderick, T. T., & Mulkern, K. M. (2005). "New behavioral paradigms for virtual human models". SAE Technical Paper Series 723-729. doi:10.4271/2005-01-2689. 
  3. ↑ Zhang, X., & Chaffin, D. B. (2005). "Digital human modeling for computer-aided ergonomics. In W. S. Marras & W. Karwowski (Eds.)". The Occupational Ergonomics Handbook: 1–20. 
  4. ↑ "Siemens Jack". https://www.plm.automation.siemens.com/media/store/en_us/4917_tcm1023-4952_tcm29-1992.pdf. 
  5. ↑ "Human Solutions - Products - RAMSIS Automotive". https://www.human-solutions.com/en/products/ramsis-automotive/index.html. 
  6. ↑ "Santos® Pro Experience" (in en-US). 2016-06-20. https://www.santoshumaninc.com/news/santos-pro-experience/. 
  7. ↑ "3DSSPP Software | Center for Ergonomics" (in en). https://c4e.engin.umich.edu/tools-services/3dsspp-software/. 
  8. ↑ "NexGen Ergonomics - Products - HumanCAD". http://www.nexgenergo.com/ergonomics/humancad.html. 
  9. ↑ "AnyBody Technology" (in en-US). https://www.anybodytech.com/. 
  10. ↑ "Simcenter Madymo" (in en). https://plm.sw.siemens.com/en-US/simcenter/mechanical-simulation/madymo/. 
  11. ↑ Systèmes, Dassault. "Real-time Interaction for DELMIA V5 Human (RTID) by HAPTION" (in en). https://www.3ds.com/partners/solutions/SIT000039_PDT00000001269_Real_time_Interaction_for_DELMIA_V5_Human__RTID_. 
  12. ↑ "IPS IMMA" (in en). https://industrialpathsolutions.se/ips-imma/. 


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