A thermoregulation model based on the physical and physiological characteristics of Chinese elderly
Given the increasing aging population and rising living standards in China, developing an accurate and straightforward thermoregulation model for the elderly has become increasingly essential. To address this need, an existing one-segment four-node thermoregulation model for the young was selected as the base model. This study developed the base model considering age-related physical and physiological changes to predict mean skin temperatures of the elderly. Measured data for model optimization were collected from 24 representative healthy Chinese elderly individuals (average age: 67 years). The subjects underwent temperature step changes between neutral and warm conditions with a temperature range of 25–34 °C. The model's demographic representation was first validated by comparing the subjects' physical characteristics with Chinese census data. Secondly, sensitivity analysis was performed to investigate the influences of passive system parameters on skin and core temperatures, and adjustments were implemented using measurement or literature data specific to the Chinese elderly. Thirdly, the active system was modified by resetting the body temperature set points. The active parameters to control thermoregulation activities were further optimized using the TPE (Tree-structured Parzen Estimator) hyperparameter tuning method. The model's accuracy was further verified using independent experimental data for a temperature range of 18–34 °C for Chinese elderly. By comprehensively considering age-induced thermal response changes, the proposed model has potential applications in designing and optimizing thermal management systems in buildings, as well as informing energy-efficient strategies tailored to the specific needs of the Chinese elderly population.
Funding
National Key R&D Program of China [Grant No: 2022YFC3801504]
Natural Science Foundation of Chongqing, China [Grant No: cstc2021ycjh-bgzxm0156]
Chinese Scholarship Council [No: 202206050102]
History
School
- Design and Creative Arts
Department
- Design
Published in
Computers in Biology and MedicineVolume
172Publisher
Elsevier BVVersion
- AM (Accepted Manuscript)
Rights holder
© Elsevier LtdPublisher statement
This paper was accepted for publication in the journal Computers in Biology and Medicine and the definitive published version is available at https://doi.org/10.1016/j.compbiomed.2024.108262Acceptance date
2024-03-06Publication date
2024-03-07Copyright date
2024ISSN
0010-4825eISSN
1879-0534Publisher version
Language
- en