000000885 001__ 885
000000885 005__ 20260120144840.0
000000885 0247_ $$2DOI$$a10.6083/M4833Q22
000000885 037__ $$aETD
000000885 245__ $$aEEG-based cognitive load estimation
000000885 260__ $$bOregon Health and Science University
000000885 269__ $$a2013
000000885 336__ $$aThesis
000000885 502__ $$bM.S.
000000885 502__ $$gBiomedical Engineering
000000885 520__ $$aMonitoring cognitive effort is challenging due to complex neural networks and variability in task engagement. This study presents an electroencephalogram (EEG) and machine learning-based approach to estimate cognitive effort during listening tasks. We developed an EEG processing pipeline incorporating a novel method for separating ocular artifacts from cortical signals and evaluated multiple classification strategies. While alternative classifiers performed similarly to prior research, they highlighted limitations of current approaches. Extending EEG-based cognitive load estimation to a new population, we applied the system to individuals with aphasia and controls during naturalistic listening tasks of varying complexity. The system distinguished EEG data from difficult versus easy passages in both groups, though classification accuracy was lower than in previous studies, likely due to subtle task manipulations and inconsistent effort levels. These findings inform future refinements for cognitive monitoring in clinical populations.
000000885 540__ $$fCC BY
000000885 542__ $$fIn copyright - single owner
000000885 650__ $$aMachine Learning$$011449
000000885 650__ $$aArtificial Intelligence$$015109
000000885 650__ $$aElectroencephalography$$018287
000000885 650__ $$aAphasia$$014975
000000885 650__ $$aCognition$$016868
000000885 650__ $$aSignal Processing, Computer-Assisted$$025995
000000885 691__ $$aSchool of Medicine$$041369
000000885 692__ $$aDepartment of Biomedical Engineering$$041397
000000885 7001_ $$aQuinn, Max$$uOregon Health and Science University$$041354
000000885 8564_ $$94eae8c52-b0de-4d6f-a66f-f935a8bb2525$$s1368767$$uhttps://digitalcollections.ohsu.edu/record/885/files/888_etd.pdf$$ePublic$$23a6c0ddffe27ec46399988344e1c06ee$$31
000000885 905__ $$a/rest/prod/0c/48/3j/41/0c483j41b
000000885 909CO $$ooai:digitalcollections.ohsu.edu:885$$pstudent-work
000000885 956__ $$aGet Accessible Copy$$uhttps://ohsu.libwizard.com/f/requestaccessibledocument
000000885 980__ $$aTheses and Dissertations