DEMONSTRATING THE FEASIBILITY OF MULTIMODAL NEUROIMAGING DATA CAPTURE WITH A WEARABLE ELECTOENCEPHALOGRAPHY + FUNCTIONAL NEAR-INFRARED SPECTROSCOPY (EEG+FNIRS) IN SITU

Dybvik, Henrikke; Erichsen, Christian Kuster; Steinert, Martin · 2021 · Crossref

DOI: 10.1017/pds.2021.90

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Summary

This paper addresses the trade-off between experimental control and ecological validity in engineering design research, specifically regarding the measurement of human cognition. While laboratory settings offer control, they often fail to replicate real-world conditions where technology is used. To bridge this gap, the authors developed and tested a low-cost, wearable multimodal neuroimaging setup combining electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). The study aims to demonstrate the feasibility of capturing high-quality neural data in situ, thereby enabling researchers to investigate cognitive processes like cognitive load in naturalistic environments. The methodology involved integrating a wearable EEG system with an fNIRS device featuring 40 channels over the prefrontal cortex. Data processing included power spectral density analysis for EEG and general linear model regression with autoregressive pre-whitening for fNIRS to mitigate motion and physiological artifacts. The authors validated the setup through three distinct use cases of increasing complexity: a conventional human-computer interaction task involving a computer game with varying difficulty levels; an in situ driving experiment comparing city and highway driving; and an in situ Ashtanga Vinyasa yoga practice involving significant physical movement. The results confirmed the setup’s ability to detect cognitive load across all scenarios. In the computer game experiment, increased difficulty correlated with expected increases in frontal theta power and decreases in central/posterior alpha power, alongside increased oxygenated hemoglobin concentrations in fNIRS data. In the driving experiment, EEG data indicated higher cognitive load during city driving compared to highway driving and baseline, consistent with the hypothesis that complex environments demand more attention. However, fNIRS data suggested lower cognitive demand during highway driving than at baseline, which the authors attribute to mental fatigue. In the yoga experiment, while significant motion artifacts were present, statistical models and filtering techniques allowed for the extraction of usable trend data, demonstrating robustness against movement. The significance of this work lies in proving that affordable, wearable multimodal neuroimaging is viable for in situ design research. The study provides practical guidelines for identifying data quality issues, such as crosstalk and motion artifacts, and offers strategies for mitigation. By validating the setup in diverse, ecologically valid contexts, the authors expand the methodological toolkit for design researchers, enabling the investigation of cognitive processes during sketching, product evaluation, and collaborative design activities in real-world settings. This approach facilitates a deeper understanding of user-centered design by capturing neural responses in the actual contexts of technology use.

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• neuro workload indices

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• Empirical Findings: physiological data