Enhancing human system performance through digital human modeling

通过数字人体建模增强人体系统性能

• 批准号: RGPIN-2018-04483
• 负责人: Fischer, Steven
• 金额: $ 2.62万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=713073
• 关键词: Enhancing; human; system; performance; through

Human factors and ergonomics (HF ment configurations. Human testing takes time, is costly, and can limit the number of designs or equipment configurations that can be explored. With advances in computer simulation and animation, users are beginning to explore digital human models (DHM), or "virtual workers", to evaluate equipment, products and workplaces from an HF a lack of well-trained highly qualified personnel (HQP) with expertise in DHM, and a lack of fundamental knowledge on the validity and sensitivity of DHMs to elicit realistic movement behaviour predictions under changing person (e.g., gender, body mass, etc.) and task (e.g., body-borne load, encumbrance) related constraints. This program of research applies a constraints-based theoretical framework and novel movement characterization approach to advance our fundamental knowledge about how person and task related factors influence movement behaviours in an occupational context. Moreover, by integrating empirical and computational (DHM) evidence, my HQP and I will determine if movement behaviours are adjusted, when constrained by person and task factors, by tuning performance objectives. Currently, our Canadian Armed Forces have limited information available to inform decisions about what type of equipment soldiers should wear, how much load they can carry, or what type of body armour is most effective to optimize soldier effectiveness while minimizing solder burden (i.e., biomechanical consequences associated with injury). In the next five years, my team and I will systematically uncover how person and task related factors affect movement behaviors, using tasks relevant to military as a starting point. This knowledge can be applied to tune and validate the performance objectives that drive DHM--based simulations, or “virtual soldiers”. Validated “virtual soldiers” can be used to proactively identify preferred equipment designs and configurations most likely to optimize solider effectiveness. In addition, my HQP will develop advanced and marketable proficiency in DHM, addressing a current void of DHM expertise in today's workforce. My HQP will be trained to deploy DHM-based simulations to tackle work-related injury concerns more broadly across sectors including healthcare, manufacturing and service sectors.

人为因素和人体工程学（HF的配置。人体测试需要时间高昂，可以限制可以探索的设计或设备配置的数量。随着计算机模拟和动画的进步，用户开始探索数字人类模型（DHM），或“虚拟工人”，或者从缺乏良好的人（QUS）（QUD）（QUS）中的“虚拟工人”（Virtual Worker），并涉及良好的人（HF）（QUS）（QUD）（QUD）（QU）缺乏良好的人（HF）（HF）（QQ）（HF）（QUD）（QU）（QU）的专家（HF）（QU）（HF）（QU）（QU）（QU）（QU）缺乏良好的人（HF）（QQ）。关于DHM的有效性和敏感性的基本知识会在变化的人（例如，性别，身体质量等）和任务（例如，体内载荷，占用范围）下进行研究，该计划的相关框架采取了基于理论的特征，以推动我们的运动相关方面，经验和计算（DHM）证据，我和我的HQP将通过调整绩效目标来确定运动行为是否在受人和任务因素约束时调整了运动行为。 目前，我们的加拿大武装部队的信息有限，可以告知士兵应磨损哪种类型的设备，他们可以承担多少载荷或哪种类型的防弹衣可以优化士兵有效性，同时最大程度地减少焊料燃烧（即与伤害相关的生物力学后果）。在接下来的五年中，我和我的团队将系统地发现与人与任务相关的因素如何影响运动行为，并使用与军事相关的任务作为起点。这些知识可以应用于调整和验证驱动基于DHM的模拟或“虚拟士兵”的性能目标。经过验证的“虚拟士兵”可用于主动识别最有可能优化居师效力的首选设备设计和配置。此外，我的HQP将在DHM中发展高级且可销售的水平，以解决当前DHM专业知识的问题。我的HQP将接受基于DHM的模拟培训，以更广泛地解决与工作有关的伤害问题，包括医疗保健，制造业和服务部门。