CHS: Small: Evaluating and Optimizing Wayfinding in Healthcare Settings through Biometric Data and Virtual Response Testing

CHS：小型：通过生物识别数据和虚拟响应测试评估和优化医疗保健环境中的寻路

• 批准号: 2008501
• 负责人: Saleh Kalantari
• 金额: $ 41.57万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-15 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2008501&HistoricalAwards=false
• 关键词: CHS; Small; Evaluating; Optimizing; Wayfinding

Wayfinding systems are the signs, color-schemes, and other features of large, complex buildings that serve as aids in navigation. Unfortunately, wayfinding is often treated as an "afterthought" rather than as an integral part of the architectural design process. In healthcare facilities, difficulties in wayfinding have been shown to be a major source of stress for patients and visitors, as well as a significant burden on hospital staff members and an obstacle to operational efficiency. Testing and evaluating wayfinding systems is difficult, because each facility is unique and trying out many different wayfinding options in the same building to see which one works best would be financially and logistically implausible. Thus, there is currently no good method to rigorously compare the success of different wayfinding design strategies. To help solve this problem, the researchers will develop a new platform to evaluate and optimize wayfinding design in specific healthcare facilities before those wayfinding features are physically constructed. Virtual-reality (VR) testing will be used to accomplish this purpose. Participants in the study will don VR headsets, along with various biometric sensors to help evaluate their stress levels. They will then be asked to complete common navigational tasks in a virtual replica of a hospital building, such as finding their way from the main entrance to a specific patient room. Using a virtual replica of the building allows the researchers to easily swap out different wayfinding features, thereby determining what types of navigational aids are most effective for improving wayfinding and reducing stress. The study will contribute to the development of a new type of research platform that can be used to conduct human-response testing for many different environmental design variables, even beyond wayfinding. It will promote greater attention to the needs of building users, including minority experiences (such as those of disabled users) that have been historically overlooked in design. The ultimate goal of the project is to streamline the virtual design-testing process so that other designers and researchers can easily implement this approach and benefit from rigorous pre-construction testing.The VR testing platform designed and developed as part of this project will use actual design information for planned hospital complexes, importing the data directly from commonly used designed-industry software. Study participants will experience different versions of the facilities that integrate different combinations of possible wayfinding designs. As the participants complete wayfinding tasks in the virtual buildings, the researchers will collect biometric data including electroencephalography (EEG) and electrocardiography (EKG) signals to serve as objective measures of stress and confusion, as well as behavioral data about the participants’ actions in the environment and their navigational success. Self-reported data about conscious evaluations and reactions to the environment will also be collected from the participants. Two pilot studies will be conducted in the context of a healthcare facility that is currently under contract by the research team’s industry partners, testing actual wayfinding designs that may be used in the final constructed facility. The first pilot study will focus on different types and combinations of color patterns, pictograms, and architectural features for wayfinding. The second pilot study will focus on the wayfinding impact of different external view conditions (the placement of windows and various exterior landmarks). As part of the research, the team will investigate and confirm brain activity (EEG) classifiers, i.e., neural signatures, for wayfinding success, by triangulating this data with the behavioral and self-reported findings. By using these neural signatures and other biometric interpretations, the project will provide specific findings to improve the facility being investigated in the pilot tests. These results will be incorporated in a platform that will be made available to other researchers as a generalized software tool to support VR-based design testing with integrated biometric sensor data. In future work, the research platform can be extended to study other implementations of wayfinding design in different types of facilities, and potentially to examine human responses to a broad range of additional design variables. Rigorous virtual testing of architectural designs has the potential to greatly expand the evidence-based design paradigm, promoting responsible, data-driven innovation in the field and leading to more effective and healthy built environments.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

寻路系统是大型复杂建筑物的标志、配色方案和其他功能，可以作为导航辅助工具。不幸的是，寻路通常被视为“事后考虑”，而不是建筑设计过程中不可或缺的一部分。在医疗设施中，认路困难已被证明是患者和来访者的主要压力来源，也是医院工作人员的重大负担和业务效率的障碍。测试和评估寻路系统是困难的，因为每个设施都是独一无二的，而且在同一栋建筑中尝试许多不同的寻路方案，以确定哪一个效果最好，在财务和后勤上都是不可信的。因此，目前还没有很好的方法来严格比较不同寻路设计策略的成功。为了帮助解决这个问题，研究人员将开发一个新的平台，在物理构建这些寻路功能之前，评估和优化特定医疗机构的寻路设计。将使用虚拟现实(VR)测试来实现这一目的。这项研究的参与者将戴上VR耳机，以及各种生物识别传感器，以帮助评估他们的压力水平。然后，他们将被要求在医院建筑的虚拟复制品中完成常见的导航任务，例如从正门到特定病房的路线。通过使用建筑物的虚拟复制品，研究人员可以轻松地交换不同的寻路功能，从而确定哪种类型的导航辅助设备在改进寻路和减轻压力方面最有效。这项研究将有助于开发一种新型的研究平台，可以用来对许多不同的环境设计变量进行人体响应测试，甚至超越路线识别。它将促进更多地关注建筑用户的需求，包括在设计中历来被忽视的少数群体体验(如残疾用户的体验)。该项目的最终目标是简化虚拟设计测试流程，以便其他设计师和研究人员可以轻松实施这种方法，并从严格的施工前测试中受益。作为该项目的一部分，设计和开发的VR测试平台将使用规划的医院综合体的实际设计信息，直接从常用的设计行业软件导入数据。研究参与者将体验不同版本的设施，这些设施整合了可能的路线设计的不同组合。随着参与者在虚拟建筑中完成寻路任务，研究人员将收集包括脑电(EEG)和心电(EKG)信号在内的生物特征数据，作为压力和困惑的客观衡量标准，以及关于参与者在环境中的行为和导航成功的行为数据。还将从参与者那里收集关于有意识的评估和对环境的反应的自我报告数据。两项试点研究将在一个医疗设施的背景下进行，该设施目前正与研究团队的行业合作伙伴签订合同，测试可能在最终建成的设施中使用的实际路线设计。第一项初步研究将侧重于不同类型和组合的颜色图案、象形文字和建筑特征以供认路。第二项初步研究将侧重于不同外部景观条件(窗户和各种外部地标的位置)对寻路的影响。作为研究的一部分，该团队将通过将这些数据与行为和自我报告的发现进行三角测量，来调查和确认大脑活动(EEG)分类器，即神经特征，以获得成功的路线。通过使用这些神经特征和其他生物统计学解释，该项目将提供具体的发现，以改善在试点测试中正在调查的设施。这些结果将被合并到一个平台中，该平台将作为通用软件工具提供给其他研究人员，以支持基于VR的设计测试和集成的生物特征传感器数据。在未来的工作中，研究平台可以扩展到研究不同类型设施中路线识别设计的其他实现，并可能检查人类对广泛的附加设计变量的反应。建筑设计的严格虚拟测试有可能极大地扩展基于证据的设计范式，促进该领域负责任的、数据驱动的创新，并带来更有效和更健康的建筑环境。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。