Bayesian Inference of Hidden Cognitive Performance and Arousal States in Presence of Music
<italic>Goal:</italic> Poor arousal management may lead to reduced cognitive performance. Specifying a model and decoder to infer the cognitive arousal and performance contributes to arousal regulation via non-invasive actuators such as music. <italic>Methods:</italic> We emp...
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| Format: | Article |
| Language: | English |
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IEEE
2024-01-01
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| Series: | IEEE Open Journal of Engineering in Medicine and Biology |
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| Online Access: | https://ieeexplore.ieee.org/document/10474164/ |
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| _version_ | 1832582339938484224 |
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| author | Saman Khazaei Md Rafiul Amin Maryam Tahir Rose T. Faghih |
| author_facet | Saman Khazaei Md Rafiul Amin Maryam Tahir Rose T. Faghih |
| author_sort | Saman Khazaei |
| collection | DOAJ |
| description | <italic>Goal:</italic> Poor arousal management may lead to reduced cognitive performance. Specifying a model and decoder to infer the cognitive arousal and performance contributes to arousal regulation via non-invasive actuators such as music. <italic>Methods:</italic> We employ a Bayesian filtering approach within an expectation-maximization framework to track the hidden states during the <inline-formula><tex-math notation="LaTeX">$n$</tex-math></inline-formula>-back task in the presence of calming and exciting music. We decode the arousal and performance states from the skin conductance and behavioral signals, respectively. We derive an arousal-performance model based on the Yerkes—Dodson law. We design a performance-based arousal decoder by considering the corresponding performance and skin conductance as the observation. <italic>Results:</italic> The quantified arousal and performance are presented. The existence of Yerkes—Dodson law can be interpreted from the arousal-performance relationship. Findings display higher matrices of performance within the exciting music. <italic>Conclusions:</italic> The performance-based arousal decoder has a better agreement with the Yerkes—Dodson law. Our study can be implemented in designing non-invasive closed-loop systems. |
| format | Article |
| id | doaj-art-d726233deaf1406abe1e173f1a94eb70 |
| institution | Kabale University |
| issn | 2644-1276 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of Engineering in Medicine and Biology |
| spelling | doaj-art-d726233deaf1406abe1e173f1a94eb702025-01-30T00:03:44ZengIEEEIEEE Open Journal of Engineering in Medicine and Biology2644-12762024-01-01562763610.1109/OJEMB.2024.337792310474164Bayesian Inference of Hidden Cognitive Performance and Arousal States in Presence of MusicSaman Khazaei0https://orcid.org/0000-0002-9463-9782Md Rafiul Amin1https://orcid.org/0000-0003-4680-3071Maryam Tahir2https://orcid.org/0000-0002-1719-9170Rose T. Faghih3https://orcid.org/0000-0001-5117-2628Department of Biomedical Engineering, New York University, New York, NY, USADepartment of Electrical and Computer Engineering, University of Houston, Houston, TX, USADepartment of Electrical and Computer Engineering, University of Houston, Houston, TX, USADepartment of Biomedical Engineering, New York University, New York, NY, USA<italic>Goal:</italic> Poor arousal management may lead to reduced cognitive performance. Specifying a model and decoder to infer the cognitive arousal and performance contributes to arousal regulation via non-invasive actuators such as music. <italic>Methods:</italic> We employ a Bayesian filtering approach within an expectation-maximization framework to track the hidden states during the <inline-formula><tex-math notation="LaTeX">$n$</tex-math></inline-formula>-back task in the presence of calming and exciting music. We decode the arousal and performance states from the skin conductance and behavioral signals, respectively. We derive an arousal-performance model based on the Yerkes—Dodson law. We design a performance-based arousal decoder by considering the corresponding performance and skin conductance as the observation. <italic>Results:</italic> The quantified arousal and performance are presented. The existence of Yerkes—Dodson law can be interpreted from the arousal-performance relationship. Findings display higher matrices of performance within the exciting music. <italic>Conclusions:</italic> The performance-based arousal decoder has a better agreement with the Yerkes—Dodson law. Our study can be implemented in designing non-invasive closed-loop systems.https://ieeexplore.ieee.org/document/10474164/Affective computingbiomedical signal processingestimationstate-space methods |
| spellingShingle | Saman Khazaei Md Rafiul Amin Maryam Tahir Rose T. Faghih Bayesian Inference of Hidden Cognitive Performance and Arousal States in Presence of Music IEEE Open Journal of Engineering in Medicine and Biology Affective computing biomedical signal processing estimation state-space methods |
| title | Bayesian Inference of Hidden Cognitive Performance and Arousal States in Presence of Music |
| title_full | Bayesian Inference of Hidden Cognitive Performance and Arousal States in Presence of Music |
| title_fullStr | Bayesian Inference of Hidden Cognitive Performance and Arousal States in Presence of Music |
| title_full_unstemmed | Bayesian Inference of Hidden Cognitive Performance and Arousal States in Presence of Music |
| title_short | Bayesian Inference of Hidden Cognitive Performance and Arousal States in Presence of Music |
| title_sort | bayesian inference of hidden cognitive performance and arousal states in presence of music |
| topic | Affective computing biomedical signal processing estimation state-space methods |
| url | https://ieeexplore.ieee.org/document/10474164/ |
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