基于认知负荷测量的设计知识推送时间识别

IF 5.4 2区 医学 Q2 MATERIALS SCIENCE, BIOMATERIALS
Yafei Nie , Shurong Tong , Jing Li , Yicha Zhang , Chen Zheng , Bin Fan
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引用次数: 4

摘要

随着市场竞争的日益激烈,多学科设计知识的再利用在产品开发中显得尤为重要。它可以帮助设计师,特别是那些缺乏足够经验的设计师,做出正确的决策,实现快速设计。传统上,设计师主要通过信息检索来获取设计知识,这种方法通常耗时且效率低下。为了克服传统知识检索方法的不足,积极地为设计人员提供所需的知识,知识推送被广泛认为是一种解决方案。然而,在设计过程中及时向设计师推送所需的知识仍然是一项具有挑战性的任务。为此,本文提出了一种基于认知负荷测量的时间识别方法来识别设计知识推送的合适时间。首先,通过研究认知负荷对三种行为(鼠标动态、击键动态和情绪状态)的影响,确定了与认知负荷变化相关的行为指标。其次,通过行为观察考察同时不引人注目地跟踪上述三种行为来推断认知负荷的可能性和有效性。最后,利用分类算法研究了基于认知负荷的知识推送时间预测。实验结果表明,该方法对认知负荷的预测准确率为55%,对推送时间的预测准确率为83%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Time identification of design knowledge push based on cognitive load measurement

The reuse of multidisciplinary design knowledge is pivotal in product development because of the increasingly fierce market competition. It can assist designers, particularly those who lack sufficient experience, in making correct decisions and achieving rapid design. Traditionally, designers primarily acquire design knowledge through information retrieval, which is typically time-consuming and inefficient. A solution that is widely considered to overcome the deficiencies of traditional knowledge retrieval approaches and actively provide designers with necessary knowledge is knowledge push. However, achieving the timely push of required knowledge to designers during the design process remains a challenging task. Accordingly, this paper presents a time identification method based on cognitive load measurement to identify the suitable time for design knowledge push. First, behavioral indicators related to the changes in cognitive load are identified by investigating the influence of the load on three types of behaviors: mouse dynamics, keystroke dynamics, and emotional states. Second, the possibility and efficacy of inferring the cognitive load by simultaneously and unobtrusively tracking the three aforementioned behaviors are considered through behavioral observations. Finally, predicting the knowledge push time based on the cognitive load using classification algorithms is investigated. The experimental results indicate that the accuracy of the proposed method in inferring the cognitive load is 55%, and that of push time is 83%.

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来源期刊
ACS Biomaterials Science & Engineering
ACS Biomaterials Science & Engineering Materials Science-Biomaterials
CiteScore
10.30
自引率
3.40%
发文量
413
期刊介绍: ACS Biomaterials Science & Engineering is the leading journal in the field of biomaterials, serving as an international forum for publishing cutting-edge research and innovative ideas on a broad range of topics: Applications and Health – implantable tissues and devices, prosthesis, health risks, toxicology Bio-interactions and Bio-compatibility – material-biology interactions, chemical/morphological/structural communication, mechanobiology, signaling and biological responses, immuno-engineering, calcification, coatings, corrosion and degradation of biomaterials and devices, biophysical regulation of cell functions Characterization, Synthesis, and Modification – new biomaterials, bioinspired and biomimetic approaches to biomaterials, exploiting structural hierarchy and architectural control, combinatorial strategies for biomaterials discovery, genetic biomaterials design, synthetic biology, new composite systems, bionics, polymer synthesis Controlled Release and Delivery Systems – biomaterial-based drug and gene delivery, bio-responsive delivery of regulatory molecules, pharmaceutical engineering Healthcare Advances – clinical translation, regulatory issues, patient safety, emerging trends Imaging and Diagnostics – imaging agents and probes, theranostics, biosensors, monitoring Manufacturing and Technology – 3D printing, inks, organ-on-a-chip, bioreactor/perfusion systems, microdevices, BioMEMS, optics and electronics interfaces with biomaterials, systems integration Modeling and Informatics Tools – scaling methods to guide biomaterial design, predictive algorithms for structure-function, biomechanics, integrating bioinformatics with biomaterials discovery, metabolomics in the context of biomaterials Tissue Engineering and Regenerative Medicine – basic and applied studies, cell therapies, scaffolds, vascularization, bioartificial organs, transplantation and functionality, cellular agriculture
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