The effect of cognitive emotional states on physiological productivity

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dc.authorid0000-0002-6004-7201
dc.authorid0000-0002-7134-3997
dc.contributor.authorDalfidan, Derya D.
dc.contributor.authorGunduz, Tulin
dc.date.accessioned2026-02-08T15:15:31Z
dc.date.available2026-02-08T15:15:31Z
dc.date.issued2025
dc.departmentBursa Teknik Üniversitesi
dc.description.abstractEmotional states are fundamental attributes distinguishing humans from machines, and productivity represents one of the primary life objectives for this emotionally driven being. However, existing research on productivity and job performance frequently underestimates the impact of underlying emotional mechanisms. Thus, a systematic examination of the emotion-productivity interface is essential to clarify the psychophysiological processes that regulate work efficiency. In this study, emotional induction was achieved through a curated video stimulus set designed to evoke positive (happiness) and negative (sadness) responses in 39 participants, followed by a computer-based Stroop task. Electroencephalography (EEG) was employed to capture emotional states within the two-dimensional valence-arousal framework. During task performance, parameters related to productivity metrics were recorded. Three machine learning models - Artificial Neural Networks (ANN), Support Vector Machines (SVM), and Random Forest (RF) - were implemented to predict productivity levels. For positive emotions, mean absolute error (MAE) values were 0.1031 (ANN), 0.0760 (SVM), and 0.0721 (RF). For negative emotions, the values were 0.1165, 0.0902, and 0.0659, respectively. Results demonstrated that productivity levels increased during tasks performed after the induction of positive emotions. Overall, this study provides empirical evidence that productivity can be predicted from emotional states, emphasizing their integral role in cognitive processes and their potential utility for optimizing workplace performance.
dc.identifier.doi10.1080/00207454.2025.2593393
dc.identifier.issn0020-7454
dc.identifier.issn1563-5279
dc.identifier.pmid41273292
dc.identifier.scopus2-s2.0-105024881786
dc.identifier.scopusqualityQ3
dc.identifier.urihttps://doi.org/10.1080/00207454.2025.2593393
dc.identifier.urihttps://hdl.handle.net/20.500.12885/5826
dc.identifier.wosWOS:001635558400001
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherTaylor & Francis Ltd
dc.relation.ispartofInternational Journal of Neuroscience
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzWOS_KA_20260207
dc.subjectNeuroergonomics
dc.subjectproductivity
dc.subjectemotion recognition
dc.subjectEEG
dc.subjectmachine learning
dc.titleThe effect of cognitive emotional states on physiological productivity
dc.typeArticle

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