Aiming to help researchers capture output from the early stages of engineering design projects, this article presents a new research tool for digitally capturing physical prototypes. The motivation for this work is to collect observations that can aid in understanding prototyping in the early stages of engineering design projects, and this article investigates if and how digital capture of physical prototypes can be used for this purpose. Early-stage prototypes are usually rough and of low fidelity and are thus often discarded or substantially modified through the projects. Hence, retrospective access to prototypes is a challenge when trying to gather accurate empirical data. To capture the prototypes developed through the early stages of a project, a new research tool has been developed for capturing prototypes through multi-view images, along with metadata describing by whom, why, when, and where the prototypes were captured. Over the course of 17 months, this research tool has been used to capture more than 800 physical prototypes from 76 individual users across many projects. In this article, one project is shown in detail to demonstrate how this capturing system can gather empirical data for enriching engineering design project cases that focus on prototyping for concept generation. The authors also analyze the metadata provided by the system to give understanding into prototyping patterns in the projects. Lastly, through enabling digital capture of large quantities of data, the research tool presents the foundations for training artificial intelligence-based predictors and classifiers that can be used for analysis in engineering design research.

The early (pre-requirement) stages of product development can provide relevant insights into the creative design process. At these stages, the communication of ideas during the prototyping process can serve as a rich source for information. In this paper, we attempt to document physical prototypes generated during the design process. We describe the design and preliminary testing of Protobooth Oulu: a system that can be used for documenting the process of prototyping products through capturing process output 'snapshots' in time at the early stages of product development. Our primary motivation is to facilitate documentation and reflection from an educational perspective. We tested the system during a course on digital fabrication in a FabLab environment, where ten teams documented their coursework over the course of six weeks. Managing to capture prototypes over time, analysis of the captured data showed evolution and major changes in the prototypes. Such data can be used for understanding the process of prototyping and consequently provide means to improve prototype and overall creative performance. We outline a future Protobooth system in terms of functionality.

Paralympic rowers with functional impairments of the legs and trunk rely on appropriate seat configurations for performance. We compared performance, physiology, and biomechanics of an elite Paralympic rower competing in the PR1 class during ergometer rowing in a seat with three different seat and backrest inclination configurations. Unlike able-bodied rowers, PR1 rowers are required to use a seat with a backrest. For this study, we examined the following seat/backrest configurations: conA: 7.5°/25°, conB: 0°/25°, and conC: 0°/5° (usually used by the participant). All data was collected on a single day, i.e., in each configuration, one 4-min submaximal (100 W) and one maximal (all-out) stage was performed. The rowing ergometer provided the average power and (virtual) distance of each stage, while motion capture provided kinematic data, a load cell measured the force exerted on the ergometer chain, and an ergospirometer measured oxygen uptake (V˙O2). Where appropriate, a Friedman's test with post-hoc comparisons performed with Wilcoxon signed-ranked tests identified differences between the configurations. Despite similar distances covered during the submaximal intensity (conA: 793, conB: 793, conC: 787 m), the peak force was lower in conC (conA: 509, conB: 458, conC: 312 N) while the stroke rate (conA: 27 conB: 31, conC: 49 strokes·min−1) and V˙O2 (conA: 34.4, conB: 35.4, conC: 39.6 mL·kg−1·min−1) were higher. During the maximal stage, the virtual distances were 7–9% longer in conA and conB, with higher peak forces (conA: 934 m, 408 N, conB: 918 m, 418 N, conC: 856 m, 331 N), and lower stroke rates (conA: 51, conB: 54, conC: 56 strokes·min−1), though there was no difference in V˙O2peak (~47 ml−1·kg−1·min−1). At both intensities, trunk range of motion was significantly larger in configurations conA and conB. Although fatigue may have accumulated during the test day, this study showed that a more inclined seat and backrest during ergometer rowing improved the performance of a successful Paralympic PR1 rower. The considerable increase in ergometer rowing performance in one of the top Paralympic rowers in the world is astonishing and highlights the importance of designing equipment that can be adjusted to match the individual needs of Paralympic athletes.

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