School of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou, Guangdong 510641, China; Guangdong Key Laboratory of Automotive Engineering, South China University of Technology, Guangzhou, Guangdong 510641, China.
School of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou, Guangdong 510641, China; Guangdong Key Laboratory of Automotive Engineering, South China University of Technology, Guangzhou, Guangdong 510641, China.
Comput Methods Programs Biomed. 2022 Dec;227:107198. doi: 10.1016/j.cmpb.2022.107198. Epub 2022 Oct 25.
Thermal conditions are changeable in cabin space, where occupants could suffer consecutive self-thermoregulation to such changing thermal stresses. Thermal environment management is expected to be purposefully auto-adjustable for the environment by recognizing individual real-time thermal sensations. Current thermal sensation evaluation models are developed for virtual simulations rather than for realistic scenarios, challenging to evaluate human thermal sensation in the field surveys.
The study constructs a human thermal sensation model via human physiological responses to evaluate the human thermal sensation in the actual vehicle environment. The thermal sensation model forms with exponential functions to clarify the relationship between thermal sensation and pulse rate and blood pressure, which successfully expresses the approximately linear trend around neutral sensation and compensates for the end-points bias. The study set up experimental cases to determine the parameter states in the thermal sensation model. Firstly, subjective thermal sensation scoring was performed by combing with an established seven-point-scale questionnaire survey system for human thermal sensation. Wearable sensors are then applied to measure the human physiological response, including blood pressure BP, pulse rate PR and blood oxygen saturation SpO.
The subjects revealed significantly higher pulse rates (positively correlated) and lower blood pressure (negatively correlated) in the warm chamber than in the cool chamber. The defined parameter change rate effectively reveals the trend of human thermal sensation and avoids the inconsistency of raw physiological response levels. The change rate in PR and MAP between the thermal sensation in cold -3 and hot +3 is about a 10% difference.
Based on the thermal sensation model algorithm, model parameters were fitted by the subjects' thermal sensation voting and the change rate of their physiological responses. With the coefficient of determination (R) of the regression over 0.8, the proposed thermal sensation model can be employed for human thermal sensation evaluation. The physiological thermoregulatory responses effectively indicate the thermal state of the human body and can be used in thermal environments in conjunction with human smart wearable devices.
舱室内的热环境条件是多变的，居住者可能会连续进行自我热调节以适应这种不断变化的热应激。热环境管理需要通过识别个体的实时热感觉，有针对性地自动调节环境。当前的热感觉评价模型是为虚拟模拟而开发的，而不是针对实际场景，因此在现场调查中评估人体热感觉具有挑战性。
本研究通过人体对热环境的生理响应构建了人体热感觉模型，以评估实际车辆环境中的人体热感觉。热感觉模型采用指数函数形成，以阐明热感觉与脉搏率和血压之间的关系，成功地表达了中性感觉周围的近似线性趋势，并补偿了端点偏差。本研究设置了实验案例来确定热感觉模型中的参数状态。首先，通过结合已建立的七点量表问卷调查系统进行主观热感觉评分，来确定人体热感觉。然后，应用可穿戴传感器测量人体生理响应，包括血压 BP、脉搏率 PR 和血氧饱和度 SpO。
与凉爽环境相比，温暖环境中的被试者脉搏率显著升高（正相关），血压显著降低（负相关）。定义的参数变化率有效地揭示了人体热感觉的趋势，避免了原始生理响应水平的不一致性。冷-3 和热+3 之间的 PR 和 MAP 的变化率约为 10%的差异。
基于热感觉模型算法，通过被试者的热感觉投票和生理响应变化率拟合模型参数。回归的决定系数（R）超过 0.8，表明所提出的热感觉模型可用于人体热感觉评价。生理体温调节反应有效地指示人体的热状态，并可与人体智能可穿戴设备一起用于热环境中。
