January 1, 2017IEEE AccessOpen Access

Machine Learning Framework for the Detection of Mental Stress at Multiple Levels

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Population

Participants subjected to stress induced by the Montreal imaging stress task

Design

Other

Authors

ASAhmad Rauf SubhaniNational University of Sciences and Technology WMWajid MumtazCOMSATS University Islamabad MSMohamed SaadApplied Science Private University

Discussion

Member takes

Implication

ML framework detects mental stress levels with high accuracy; leaves open whether it aids cardiovascular risk stratification in practice.

Structured PICO

Population

Participants subjected to stress induced by the Montreal imaging stress task

Intervention

Machine learning framework involving electroencephalogram (EEG) signal analysis

Outcome

Accuracy for identification of stress levelssurrogate

An EEG-based machine learning framework demonstrated high accuracy in objectively quantifying mental stress levels, which may aid in developing computer-aided diagnostic tools.

Cite This Study

Subhani et al. (2017) studied this question.

synapsesocial.com/papers/6a701ec1fe4101aa97e004fa https://doi.org/10.1109/access.2017.2723622

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Machine Learning Framework for the Detection of Mental Stress at Multiple Levels

Discussion

Member takes

Implication

Structured PICO

Cite This Study

Machine Learning Framework for the Detection of Mental Stress at Multiple Levels

Discussion

Member takes

Implication

Structured PICO

Cite This Study

Also Consider

Also Consider