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Application of Functional Near-Infrared Spectroscopy to Measure Engineering Decision-Making and Design Cognition: Literature Review and Synthesis of Methods
New and disruptive building technologies will require new and disruptive ways of thinking about decision-making and design in engineering. The emergence of a novel neuroimaging technique, called functional near-infrared spectroscopy (fNIRS), provides a new approach to quantify engineering cognition. To introduce fNIRS, a systematic review was conducted to provide an overview of methods and findings. Researchers interested in measuring decision-making during infrastructure finance negotiations, coordination among stakeholders, or interaction between the built environment and human cognition will benefit from this synthesis. The review includes 32 experiments, and the mean sample size of human participants was 28. Three methods for experimental design include block, event-related, and mixed. Out of these three, block design was used in over half of the experiments. Most studies adopted band-pass or low-pass filters to remove noise and process fNIRS raw data. The most frequently used data-analysis technique to compare variables was segmenting changes in oxy-hemoglobin into different condition periods (e.g., baseline or task) or blocks (e.g., Task A or Task B) and measuring mean values, peak amplitudes, or area under the curve from different brain regions over a specific time period. However, more sophisticated statistical techniques such as General Linear Model, brain network, and interpersonal neural synchronization provide a richer explanation of cognition. This review not only introduces fNIRS as a radically new approach to study cognition in engineering but offers a guide for designing future studies. These results can be used to perform power analyses, develop hypotheses, and more quickly narrow the brain regions of interest in future empirical studies.
Application of Functional Near-Infrared Spectroscopy to Measure Engineering Decision-Making and Design Cognition: Literature Review and Synthesis of Methods
New and disruptive building technologies will require new and disruptive ways of thinking about decision-making and design in engineering. The emergence of a novel neuroimaging technique, called functional near-infrared spectroscopy (fNIRS), provides a new approach to quantify engineering cognition. To introduce fNIRS, a systematic review was conducted to provide an overview of methods and findings. Researchers interested in measuring decision-making during infrastructure finance negotiations, coordination among stakeholders, or interaction between the built environment and human cognition will benefit from this synthesis. The review includes 32 experiments, and the mean sample size of human participants was 28. Three methods for experimental design include block, event-related, and mixed. Out of these three, block design was used in over half of the experiments. Most studies adopted band-pass or low-pass filters to remove noise and process fNIRS raw data. The most frequently used data-analysis technique to compare variables was segmenting changes in oxy-hemoglobin into different condition periods (e.g., baseline or task) or blocks (e.g., Task A or Task B) and measuring mean values, peak amplitudes, or area under the curve from different brain regions over a specific time period. However, more sophisticated statistical techniques such as General Linear Model, brain network, and interpersonal neural synchronization provide a richer explanation of cognition. This review not only introduces fNIRS as a radically new approach to study cognition in engineering but offers a guide for designing future studies. These results can be used to perform power analyses, develop hypotheses, and more quickly narrow the brain regions of interest in future empirical studies.
Application of Functional Near-Infrared Spectroscopy to Measure Engineering Decision-Making and Design Cognition: Literature Review and Synthesis of Methods
Hu, Mo (author) / Shealy, Tripp (author)
2019-07-16
Article (Journal)
Electronic Resource
Unknown
DOAJ | 2021
|BASE | 2021
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