Towards cognitive fatigue detection from functional magnetic resonance imaging data
MZ Zadeh, AR Babu, JB Lim, M Kyrarini… - Proceedings of the 13th …, 2020 - dl.acm.org
Proceedings of the 13th ACM International Conference on PErvasive …, 2020•dl.acm.org
Cognitive Fatigue contributes to the degradation of performance in daily life. This work
focuses on developing an automated system to predict Cognitive Fatigue from Functional
Magnetic Resonance Imaging (fMRI) data that were collected while subjects were
performing a cognitive task. The task had multiple level of difficulty to induce cognitive load.
With the fMRI data, Machine Learning models were built to predict the fatigue level.
Preliminary results from twenty two participants show an average accuracy of 73 percent …
focuses on developing an automated system to predict Cognitive Fatigue from Functional
Magnetic Resonance Imaging (fMRI) data that were collected while subjects were
performing a cognitive task. The task had multiple level of difficulty to induce cognitive load.
With the fMRI data, Machine Learning models were built to predict the fatigue level.
Preliminary results from twenty two participants show an average accuracy of 73 percent …
Cognitive Fatigue contributes to the degradation of performance in daily life. This work focuses on developing an automated system to predict Cognitive Fatigue from Functional Magnetic Resonance Imaging (fMRI) data that were collected while subjects were performing a cognitive task. The task had multiple level of difficulty to induce cognitive load. With the fMRI data, Machine Learning models were built to predict the fatigue level. Preliminary results from twenty two participants show an average accuracy of 73 percent over k-fold cross validation.
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