A Novel Approach to Cognitive Load Measurement in N-Back Tasks Using Wearable Sensors, Empirical Mode Decomposition With Machine Learning, and Explainable AI for Feature Importance
This study introduces a novel approach for detecting mental workload and stress, utilizing ECG and Fingertip-PPG data from the MAUS dataset. The dataset includes physiological recordings such as ECG, Fingertip-PPG, Wrist-PPG, and GSR signals from 22 participants exposed to varying levels of mental w...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10817542/ |
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