Enhancing cognitive assessment through multimodal sensing: A case study using the block design test
Many cognitive assessments are limited by their reliance on relatively sparse measures of performance, like per-item accuracy or reaction time. Capturing more detailed behavioral measurements from cognitive assessments will enhance their utility in many settings, from individual clinical evaluations to large-scale research studies. We demonstrate the feasibility of combining scene and gaze cameras with supervised learning algorithms to automatically measure key behaviors on the block design test, a widely used test of visuospatial cognitive ability. We also discuss how this block-design measurement system could enhance the assessment of many critical cognitive and meta-cognitive functions such as attention, planning, progress monitoring, and strategy selection.
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Publication Date:
NSF-PAR ID:
10209949
Journal Name:
Proceedings of the 42nd Annual Meeting of the Cognitive Science Society
Page Range or eLocation-ID:
2546-2552
1. The block design test (BDT), in which a person has to recreate a visual design using colored blocks, is notable among cognitive assessments because it makes so much of a person's problem-solving strategy visible'' through their ongoing manual actions. While, for decades, numerous pockets of research on the BDT have identified certain behavioral variables as being important for certain cognitive or neurological hypotheses, there is no unifying framework for bringing together this spread of variables and hypotheses. In this paper, we identify 25 independent and dependent variables that have been examined as part of published BDT studies across many areas of cognitive science and present a sample of the research on each one. We also suggest variables of interest for future BDT research, especially as made possible with the advent of advanced recording technologies like wearable eye trackers.