Utilizing Entropy to Systematically Quantify the Resting-Condition Baroreflex Regulation Function
Baroreflex is critical to maintain blood pressure homeostasis, and the quantification of baroreflex regulation function (BRF) can provide guidance for disease diagnosis, treatment, and healthcare. Current quantification of BRF such as baroreflex sensitivity cannot represent BRF systematically. From...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2024-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2024/5514002 |
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| author | Bo-Yuan Li Xiao-Yang Li Xia Lu Rui Kang Zhao-Xing Tian Feng Ling |
| author_facet | Bo-Yuan Li Xiao-Yang Li Xia Lu Rui Kang Zhao-Xing Tian Feng Ling |
| author_sort | Bo-Yuan Li |
| collection | DOAJ |
| description | Baroreflex is critical to maintain blood pressure homeostasis, and the quantification of baroreflex regulation function (BRF) can provide guidance for disease diagnosis, treatment, and healthcare. Current quantification of BRF such as baroreflex sensitivity cannot represent BRF systematically. From the perspective of complex systems, we regard that BRF is the emergence result of fluctuate states and interactions in physiological mechanisms. Therefore, the three-layer emergence is studied in this work, which is from physiological mechanisms to physiological indexes and then to BRF. On this basis, since the entropy in statistical physics macroscopically measures the fluctuations of system’s states, in this work, the principle of maximum entropy is adopted, and a new index called PhysioEnt is proposed to quantify the fluctuations of four physiological indexes, i.e., baroreflex sensitivity, heart rate, heart rate variability, and systolic blood pressure, which aims to represent BRF in the resting condition. Further, two datasets with different subjects are analyzed, and some new findings can be obtained, such as the contributions of the physiological interactions among organs/tissues. With measurable indexes, the proposed method is expected to support individualized medicine. |
| format | Article |
| id | doaj-art-157cbe363bb14886a9639c85919a7b33 |
| institution | Kabale University |
| issn | 1099-0526 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-157cbe363bb14886a9639c85919a7b332025-02-03T11:21:06ZengWileyComplexity1099-05262024-01-01202410.1155/2024/5514002Utilizing Entropy to Systematically Quantify the Resting-Condition Baroreflex Regulation FunctionBo-Yuan Li0Xiao-Yang Li1Xia Lu2Rui Kang3Zhao-Xing Tian4Feng Ling5School of Reliability and Systems EngineeringSchool of Reliability and Systems EngineeringDepartment of NeurosurgerySchool of Reliability and Systems EngineeringDepartment of EmergencyDepartment of NeurosurgeryBaroreflex is critical to maintain blood pressure homeostasis, and the quantification of baroreflex regulation function (BRF) can provide guidance for disease diagnosis, treatment, and healthcare. Current quantification of BRF such as baroreflex sensitivity cannot represent BRF systematically. From the perspective of complex systems, we regard that BRF is the emergence result of fluctuate states and interactions in physiological mechanisms. Therefore, the three-layer emergence is studied in this work, which is from physiological mechanisms to physiological indexes and then to BRF. On this basis, since the entropy in statistical physics macroscopically measures the fluctuations of system’s states, in this work, the principle of maximum entropy is adopted, and a new index called PhysioEnt is proposed to quantify the fluctuations of four physiological indexes, i.e., baroreflex sensitivity, heart rate, heart rate variability, and systolic blood pressure, which aims to represent BRF in the resting condition. Further, two datasets with different subjects are analyzed, and some new findings can be obtained, such as the contributions of the physiological interactions among organs/tissues. With measurable indexes, the proposed method is expected to support individualized medicine.http://dx.doi.org/10.1155/2024/5514002 |
| spellingShingle | Bo-Yuan Li Xiao-Yang Li Xia Lu Rui Kang Zhao-Xing Tian Feng Ling Utilizing Entropy to Systematically Quantify the Resting-Condition Baroreflex Regulation Function Complexity |
| title | Utilizing Entropy to Systematically Quantify the Resting-Condition Baroreflex Regulation Function |
| title_full | Utilizing Entropy to Systematically Quantify the Resting-Condition Baroreflex Regulation Function |
| title_fullStr | Utilizing Entropy to Systematically Quantify the Resting-Condition Baroreflex Regulation Function |
| title_full_unstemmed | Utilizing Entropy to Systematically Quantify the Resting-Condition Baroreflex Regulation Function |
| title_short | Utilizing Entropy to Systematically Quantify the Resting-Condition Baroreflex Regulation Function |
| title_sort | utilizing entropy to systematically quantify the resting condition baroreflex regulation function |
| url | http://dx.doi.org/10.1155/2024/5514002 |
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