The Tufts fNIRS to Mental Workload (fNIRS2MW) open-access dataset is a new dataset for building machine learning classifiers that can consume a short window (30 seconds) of multivariate fNIRS recordings and predict the mental workload intensity of the user during that window. Useful Links: Project Website (and data download links): https://tufts-hci-lab.github.io/code_and_datasets/fNIRS2MW.html Code for benchmarks: https://github.com/tufts-ml/fNIRS-mental-workload-classifiers Based on moment-to-moment estimates of mental workload, the computer could adjust the interface to support the user. Publications The Tufts fNIRS Mental Workload Dataset & Benchmark for Brain-Computer Interfaces that Generalize Zhe Huang, Liang Wang, Giles Blaney, Christopher Slaughter, Devon McKeon, Ziyu Zhou, Robert
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