Check out the three latest publications in engineering design powered by iMotions.

The publications cover the following interesting topics within engineering design:

  • Predicting human operator errors to prevent accidents
  • Human concepts and design creativity during concept generation
  • Understanding decision making in engineering design situations

Dynamic Data Driven Approach for Modeling Human Error

by Wan-Lin Hu, Janette J. Meyer, Zhaosen Wang, Tahira Reid, Douglas E. Adams, Sunil Prabnakar, and Alok R. Chaturvedi

Previous research in human factor studies showed that almost 80% of accidents affecting safety, the environment and/or economics are caused by human operator errors. These errors can have many causes such as mental or physical stress in decision-making situations, especially under time pressure. This paper describes preliminary developments of a dynamic data driven platform to predict operator error and trigger appropriate intervention before the error happens. Taking advantage of the advances in commercial grade psychophysiological sensors such as electroencephalography (EEG), electrocardiogram (ECG), galvanic skin response (GSR), and eye-tracking systems, data was collected during an established protocol – the Stroop test. The experimental design began with a relaxation period, 40 questions (congruent, then incongruent) without a timer, a rest period followed by another two rounds of questions, but under increased time pressure. Measures such as workload and engagement showed responses consistent with what is expected for Stroop tests. Dynamic system analysis methods were then used to analyze the raw data using principal components analysis and the least squares complex exponential method. The results show that the algorithms have the potential to capture mental states in a mathematical fashion, thus enabling the possibility of prediction.

Reducing sketch inhibition during concept generation: Psychological evidence of the effect of interventions

by Wan-Lin Hu, Joran Booth and Tahira Reid

Concept generation is an integral part to design process and has been studied a few years. However, the effect of sketching on concept generation and thinking is still an active area of research. Sketching has for instance been shown to improve communication and visual thinking. In this study the effect of warm-up activities on cognitive states during concept generation has been investigated. Psychophysiological tools including electroencephalography (EEG) and galvanic skin response (GSR) were used along with self-report measures. All respondents in this study faced the same short design task but they had different test conditions: no warm-up activity, simple warm-up activities or sketch inhibition reducing activities. The results show that the participants who did a warm-up prior to ideation had a decrease in stress. This was especially the case for those who were not personally familiar with the design problem. It could also be seen that the art activities improved engagement for younger participants and that females reported lower mental workload. However, the number of ideas or other metrics of performance did not show any difference. It can therefore be said that warm-up activities, especially when they are art-based, are helping to reduce inhibition by calming the cognitive state.

Understanding the utilization of information stimuli in design decision making using eye gaze data

by Youyi Bi, Murtuza Shergadwala, Tahira Reid, Jitesh H. Panchal

The understanding of decision-making in engineering systems can help the designers to improve their decision-making. This knowledge enhances the research in the field and places a new focus on preference mining, decision structuring and evaluation. A lot of research has already been done in this area but there exists a research gap on how diverse information stimuli are combined by designers in decision-making. This study therefore focuses on how designers weigh different information stimuli to make decisions in engineering design contexts. The data for this study has been collected using eye gaze data from simulated engineering design tasks. The task involves optimizing an unknown function using an interface with two types of information, a graph and a list area. It could be seen that different individuals weigh the forms of information stimuli differently. The graphical information stimulus helped to optimize the function with greater accuracy.

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