The Algorithm for Predicting the Numerical Value of Salivary Cortisol Based on Heart Rate Variations in the Healthy Men
Background and purpose: The stress system is one of the most important parts of maintaining living of beings. The indices of heart rate variation (HRV) and cortisol hormone are two outputs of stress system activity. The activation of the stress system is not necessarily in a consciousness state and...
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Kurdistan University of Medical Sciences
2024-11-01
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| Series: | مجله علمی دانشگاه علوم پزشکی کردستان |
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| Online Access: | http://sjku.muk.ac.ir/article-1-7816-en.pdf |
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| author | Mohammad Reza Noruzi Marzieh Barzegar Mahdi Alizadeh Boshra Hatef |
| author_facet | Mohammad Reza Noruzi Marzieh Barzegar Mahdi Alizadeh Boshra Hatef |
| author_sort | Mohammad Reza Noruzi |
| collection | DOAJ |
| description | Background and purpose: The stress system is one of the most important parts of maintaining living of beings. The indices of heart rate variation (HRV) and cortisol hormone are two outputs of stress system activity. The activation of the stress system is not necessarily in a consciousness state and part of it is in the unconscious. The aim of this study is to provide an algorithm for predicting the numerical value of the salivary cortisol concentration using HRV indices.
Materials and methods:The samples of this study included 601 healthy adult men (between 20 and 50 years old). The used algorithms were designed to predict the numerical value of salivary cortisol taken from 9:00 AM to 2:00 PM with HRV indicators. In each of the algorithms, a predicted value is compared with the actual value to determine which was more successful.
Results: The results of this study showed that the frequency and non-linear indicators of HRV are able to predict the amount of salivary cortisol with use of Multi Layer Perceptron (MLP), XGBoost(XGB), Support Vector Machine(SVM) and Radial Basis Function(RBF) regression algorithms with the average absolute error, 7.78, 8.06, 8.37 and 7.43 percent respectively.
Conclusion: In this study, it was found that a set of linear and non-linear indicators of HRV with high power can predict the amount of salivary cortisol in the best case with a low error percentage of 7.43 by the RBF algorithm, and instead of stress self-report that does not cover the physiological part. It can be a more accurate tool in the intelligent evaluation of the stress system. |
| format | Article |
| id | doaj-art-9cce4c312e2549dca0484423fa810395 |
| institution | Kabale University |
| issn | 1560-652X 2345-4040 |
| language | fas |
| publishDate | 2024-11-01 |
| publisher | Kurdistan University of Medical Sciences |
| record_format | Article |
| series | مجله علمی دانشگاه علوم پزشکی کردستان |
| spelling | doaj-art-9cce4c312e2549dca0484423fa8103952025-02-01T09:41:40ZfasKurdistan University of Medical Sciencesمجله علمی دانشگاه علوم پزشکی کردستان1560-652X2345-40402024-11-012953748The Algorithm for Predicting the Numerical Value of Salivary Cortisol Based on Heart Rate Variations in the Healthy MenMohammad Reza Noruzi0Marzieh Barzegar1Mahdi Alizadeh2Boshra Hatef3 Department of Medical Engineering, Faculty of Engineering, Central Tehran Branch, Islamic Azad University Neuroscience Research Center, Baqiyatullah University of Medical Sciences, Tehran, Iran. AND Army University of Medical Sciences, Department of Medical Engineering, Faculty of Engineering, Central Tehran Branch, Islamic Azad University Neuroscience Research Center, Baqiyatullah University of Medical Sciences Background and purpose: The stress system is one of the most important parts of maintaining living of beings. The indices of heart rate variation (HRV) and cortisol hormone are two outputs of stress system activity. The activation of the stress system is not necessarily in a consciousness state and part of it is in the unconscious. The aim of this study is to provide an algorithm for predicting the numerical value of the salivary cortisol concentration using HRV indices. Materials and methods:The samples of this study included 601 healthy adult men (between 20 and 50 years old). The used algorithms were designed to predict the numerical value of salivary cortisol taken from 9:00 AM to 2:00 PM with HRV indicators. In each of the algorithms, a predicted value is compared with the actual value to determine which was more successful. Results: The results of this study showed that the frequency and non-linear indicators of HRV are able to predict the amount of salivary cortisol with use of Multi Layer Perceptron (MLP), XGBoost(XGB), Support Vector Machine(SVM) and Radial Basis Function(RBF) regression algorithms with the average absolute error, 7.78, 8.06, 8.37 and 7.43 percent respectively. Conclusion: In this study, it was found that a set of linear and non-linear indicators of HRV with high power can predict the amount of salivary cortisol in the best case with a low error percentage of 7.43 by the RBF algorithm, and instead of stress self-report that does not cover the physiological part. It can be a more accurate tool in the intelligent evaluation of the stress system.http://sjku.muk.ac.ir/article-1-7816-en.pdfstresssalivary cortisolheart ratemachine learningregression |
| spellingShingle | Mohammad Reza Noruzi Marzieh Barzegar Mahdi Alizadeh Boshra Hatef The Algorithm for Predicting the Numerical Value of Salivary Cortisol Based on Heart Rate Variations in the Healthy Men مجله علمی دانشگاه علوم پزشکی کردستان stress salivary cortisol heart rate machine learning regression |
| title | The Algorithm for Predicting the Numerical Value of Salivary Cortisol Based on Heart Rate Variations in the Healthy Men |
| title_full | The Algorithm for Predicting the Numerical Value of Salivary Cortisol Based on Heart Rate Variations in the Healthy Men |
| title_fullStr | The Algorithm for Predicting the Numerical Value of Salivary Cortisol Based on Heart Rate Variations in the Healthy Men |
| title_full_unstemmed | The Algorithm for Predicting the Numerical Value of Salivary Cortisol Based on Heart Rate Variations in the Healthy Men |
| title_short | The Algorithm for Predicting the Numerical Value of Salivary Cortisol Based on Heart Rate Variations in the Healthy Men |
| title_sort | algorithm for predicting the numerical value of salivary cortisol based on heart rate variations in the healthy men |
| topic | stress salivary cortisol heart rate machine learning regression |
| url | http://sjku.muk.ac.ir/article-1-7816-en.pdf |
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