https://www.selleckchem.com/pr....oducts/CI-1040-(PD18
Predicting workload using physiological sensors has taken on a diffuse set of methods in recent years. However, the majority of these methods train models on small datasets, with small numbers of channel locations on the brain, limiting a models ability to transfer across participants, tasks, or experimental sessions. In this paper, we introduce a new method of modeling a large, cross-participant and cross-session set of high density functional near infrared spectroscopy (fNIRS) data by using an approach grounded in cognitive
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