Inference-enabled tracking of acute mental stress via multi-modal wearable physiological sensing: A proof-of-concept study

• Autorzy: Zhou Yuanyuan , Mousavi Azin S. , Chalumuri Yekanth R. , Parreira Jesse D. , Modak Mihir , Sanchez-Perez Jesus Antonio , Gazi Asim H. , Inan Omer T. , Hahn Jin-Oh

Identyfikatory

DOI

10.1016/j.bbe.2024.09.004

• Języki publikacji: EN

Abstrakty

EN

Objective: To develop a novel algorithm for tracking acute mental stress which can infer acute mental stress state from multi-modal digital signatures of physiological parameters compatible with wearable-enabled sensing. Methods: We derived prominent digital signatures of physiological responses to mental stress using cross-integration of multi-modal physiological signals including the electrocardiogram (ECG), photoplethysmogram (PPG), seismocardiogram (SCG), ballistocardiogram (BCG), electrodermal activity (EDA), and respiratory effort. Then, we developed an algorithm for tracking acute mental stress that can continuously classify stress vs no stress states by computing an aggregated likelihood computed with respect to a priori probability density distributions associated with the digital signatures of mental stress under stress and no stress states. Results: Our algorithm could adequately infer mental stress state (average classification accuracy: 0.85, sensitivity: 0.85, specificity: 0.86) using a small number of prominent digital signatures derived from cross-integration of multi-modal physiological signals. The digital signatures in our work significantly outperformed the digital signatures employed in the state-of-the-art in tracking acute mental stress. Its exploitation of collective inference allowed for improved inference of mental stress state relative to naïve data mining techniques. Conclusion: Our algorithm for tracking acute mental stress has the potential to make a leap in continuous, highaccuracy, and high-confidence inference of mental stress via convenient wearable-enabled physiological sensing. Significance: The ability to continuously monitor and track mental stress can collectively improve human wellbeing.

Słowa kluczowe

EN

mental stress; collective inference; digital signature; wearable sensing; multimodal physiological sensing

PL

stres psychiczny; wnioskowanie zbiorowe; podpis cyfrowy

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2024
• Tom: Vol. 44, no. 4
• Strony: 771--781
• Opis fizyczny: Bibliogr. 46 poz., rys., tab., wykr.

Twórcy

autor

Zhou Yuanyuan

• Department of Mechanical Engineering, University of Maryland, College Park, MD, USA

autor

Mousavi Azin S.

• Department of Mechanical Engineering, University of Maryland, College Park, MD, USA

autor

Chalumuri Yekanth R.

• Department of Mechanical Engineering, University of Maryland, College Park, MD, USA

autor

Parreira Jesse D.

• Department of Mechanical Engineering, University of Maryland, College Park, MD, USA

autor

Modak Mihir

• Department of Bioengineering, University of Maryland, College Park, MD, USA

autor

Sanchez-Perez Jesus Antonio

• School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA

autor

Gazi Asim H.

• School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA

autor

Inan Omer T.

• School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA

autor

Hahn Jin-Oh

• Department of Mechanical Engineering, University of Maryland, College Park, MD, USA

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).