Measuring the Evoked Hardness of Design Problems Using Transient Microstates

Abstract

Direct interfacing of computers with the human brain is one of the holy grails of computer science and has been in the computing folklore since the very beginning of computing history. The challenges researchers are facing are non-trivial and the breakthroughs are non-negligeable. Measuring the hardness of a mental task is a fundamental problem in design sciences. In this context, the relationship between electroencephalograms (EEG) signals and the design process is an area of research with applications to the understanding of the creative process and next generation CAD/E systems. Such systems are aiming at becoming more collaborative, conceptual, creative and cognitive. We posit that the relationship between EEG signals, cognitive states and the perceived hardness of design problems is non-trivial. Different problems typically have different levels of perceived hardness. To test this, we study the use of microstate analysis to the segmentation of videos of subjects submitted to creative tasks of various difficulty. Problems and subtasks of different perceived hardness can be shown to exhibit different levels of transient microstates, a measure we have defined on the complexity of the microstate segmentation. We show that the human brain seems to be using 1–20% of its transient microstate capacity.

No time for that? An investigation of mindfulness and stress in first-year engineering design

“…Previous research has found that engineering design induces mental stress in students (Zhu et al 2007; Petkar et al 2009; Nguyen et al 2013; Nguyen & Zeng 2014, 2017; Nolte & McComb 2020, 2021) that persists even after the design task has ended (Nguyen & Zeng 2017). A detailed discussion on how stress might manifest during specific stages of the engineering process relevant to this study is included in Nolte & McComb (2021).…”

“…Engineering design is a highly cognitive process (Dym et al 2005) that can induce stress for designers (Zhu, Yao & Zeng 2007; Petkar et al 2009; Nguyen, Xu & Zeng 2013; Nguyen & Zeng 2014, 2017; Nolte & McComb 2020, 2021). The multiple skills designers must use to solve design problems (e.g., analytical and technical skills, decision-making and creativity; Dym et al 2005) and the inherent complexity of design problems (e.g., ill-defined and constantly evolving; Dym et al 2005) contribute to the cognitive stress of engineering design.…”

“…Previous research has shown that mental stress is induced during engineering design (Zhu et al 2007; Petkar et al 2009; Nguyen et al 2013; Nguyen & Zeng 2014, 2017; Nolte & McComb 2020, 2021). Not only can substantial mental stress during design unnecessarily burden novice designers, but excessive pressure during problem-solving tasks has been shown to decrease performance (Beilock et al 2004; Beilock & DeCaro 2007).…”

Review of the use of neurophysiological and biometric measures in experimental design research

“…This stream of studies has so far reached maturation in Nguyen et al (2019), in which EEG-based algorithms are tested against manual segmentation of design activities. The most effective algorithm in terms of predicting design segments, based on microstate transitions already discussed in Nguyen et al (2015), is almost indistinguishable than manual segmentation if specific statistical tools are used. However, because of the identification of different cognitive structures, algorithmic segmentation cannot be considered as a replacement for manual segmentation hitherto.…”

“…Still with reference to conceptual design, Nguyen et al (2018) use EEG to assess effort, fatigue, and concentration. Such an assessment is enabled by the results of previous scholars' studies and markedly (Nguyen et al, 2015). Based on the outcomes of the experiment, "high levels of effort occur mostly at the beginning and at the end of the design process", while some nuances of fatigue have a negative correlation with this pattern.…”