Cross dataset workload classification using encoded wavelet decomposition features
For practical applications, it is desirable for a trained classification system to be independent of task and/or subject. In this study, we show one-way transfer between two independent EEG workload datasets: from a large multitasking dataset with 48 subjects to a second Stroop test dataset with 18...
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Main Authors: | , , |
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Other Authors: | |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2021
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/145993 |
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Institution: | Nanyang Technological University |
Language: | English |