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1. Development of the data-driven thermal satisfaction prediction model as a function of human physiological responses in a built environment

   Choi, J.; Yeom, D. (January 2019, Building and environment)

   The purpose of this study is to investigate and determine the relationship between occupants’ thermal satisfaction and physiological responses in an office environment, and to estimate their thermal satisfaction level via human physiological signals. This study adapted the heart rate and seven local body skin temperatures as physiological signals, as well as human factors (gender, age, BMI), to determine establish a thermal satisfaction prediction model by combining human factors and physiological signals. The results revealed significant correlations between overall thermal satisfaction levels and local body skin temperatures, as well as heart rates. The heart rates showed a negative correlation with overall thermal satisfaction, and the skin temperature of the forehead, arm, wrist (back and front), chest, and belly also revealed a significant correlation with the thermal satisfaction levels of the study participants. This study also determined the order and priority of local skin temperatures (as well as gender and BMI) by their impact on thermal satisfaction. Considering all human physiological factors and practical application of the results, the local skin temperatures of the forehead, wrist (back), and gender demonstrated 88.52% accuracy for estimating thermal satisfaction, which provided significant validation for practical use of this procedure. 

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2. Heat Flux Sensing for Machine-Learning-Based Personal Thermal Comfort Modeling

   https://doi.org/10.3390/s19173691  

   Jung, Wooyoung; Jazizadeh, Farrokh; Diller, Thomas E. (September 2019, Sensors)

   null (Ed.)

   In recent years, physiological features have gained more attention in developing models of personal thermal comfort for improved and accurate adaptive operation of Human-In-The-Loop (HITL) Heating, Ventilation, and Air-Conditioning (HVAC) systems. Pursuing the identification of effective physiological sensing systems for enhancing flexibility of human-centered and distributed control, using machine learning algorithms, we have investigated how heat flux sensing could improve personal thermal comfort inference under transient ambient conditions. We have explored the variations of heat exchange rates of facial and wrist skin. These areas are often exposed in indoor environments and contribute to the thermoregulation mechanism through skin heat exchange, which we have coupled with variations of skin and ambient temperatures for inference of personal thermal preferences. Adopting an experimental and data analysis methodology, we have evaluated the modeling of personal thermal preference of 18 human subjects for well-known classifiers using different scenarios of learning. The experimental measurements have revealed the differences in personal thermal preferences and how they are reflected in physiological variables. Further, we have shown that heat exchange rates have high potential in improving the performance of personal inference models even compared to the use of skin temperature. 

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3. Optimizing Sensor Locations for Electrodermal Activity Monitoring Using a Wearable Belt System

   https://doi.org/10.3390/jsan14020031  

   McNaboe, Riley Q; Kong, Youngsun; Henderson, Wendy A; Cong, Xiaomei; Li, Aolan; Seo, Min-Hee; Chen, Ming-Hui; Feng, Bin; Posada-Quintero, Hugo F (April 2025, Journal of Sensor and Actuator Networks)

   Wearable devices for continuous health monitoring in humans are constantly evolving, yet the signal quality may be improved by optimizing electrode placement. While the commonly used locations to measure electrodermal activity (EDA) are at the fingers or the wrist, alternative locations, such as the torso, need to be considered when applying an integrated multimodal approach of concurrently recording multiple bio-signals, such as the monitoring of visceral pain symptoms like those related to irritable bowel syndrome (IBS). This study aims to quantitatively determine the EDA signal quality at four torso locations (mid-chest, upper abdomen, lower back, and mid-back) in comparison to EDA signals recorded from the fingers. Concurrent EDA signals from five body locations were collected from twenty healthy participants as they completed a Stroop Task and a Cold Pressor task that elicited salient autonomic responses. Mean skin conductance (meanSCL), non-specific skin conductance responses (NS.SCRs), and sympathetic response (TVSymp) were derived from the torso EDA signals and compared with signals from the fingers. Notably, TVSymp recorded from the mid-chest location showed significant changes between baseline and Stroop phase, consistent with the TVSymp recorded from the fingers. A high correlation (0.77–0.83) was also identified between TVSymp recorded from the fingers and three torso locations: mid-chest, upper abdomen, and lower back locations. While the fingertips remain the optimal site for EDA measurement, the mid-chest exhibited the strongest potential as an alternative recording site, with the upper abdomen and lower back also demonstrating promising results. These findings suggest that torso-based EDA measurements have the potential to provide reliable measurement of sympathetic neural activities and may be incorporated into a wearable belt system for multimodal monitoring. 

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4. Vision-based Thermal Comfort Quantification for HVAC Control

   Jung, W.; Jazizadeh, F. (June 2018, Building and environment)

   This study presents a vision-based approach that employs RGB video images as the sole source for inferring thermoregulation states in the human body in response to thermal condition variations in indoor environments. The primary objective is to contribute to our envisioned thermoregulation-based HVAC control that leverages actual thermal demands from end-users’ thermoregulation states for increased energy efficiency. Given that the envisioned control system calls for measurement techniques under four constraints of non-intrusiveness, applicability, sensitivity, and ubiquity (i.e., feasibility and scalability), this study investigated the potentials of ubiquitously obtainable RGB video images (through webcams or smartphones). Using photoplethysmography(PPG), a well-known optical technique for measuring blood volume changes in the microvascular bed of skin, we have leveraged the mechanism of blood flow control to the skin surface (blood vessels' dilation and constriction)for heat dissipation regulations, reflected in PPG signal's amplitude. Given the subtle variations of PPG signals and their susceptibility to noise, we proposed a framework that uses a combination of independent component analysis and adaptive filtering to reduce unwanted and in-band artifacts while preserving the amplitude information of PPG signals that indicates thermophysiological states. The framework was experimentally evaluated using transient thermal conditions to account for applicability and sensitivity attributes. Therefore, without considering an acclimation time for stabilized thermoregulation states, human subjects were exposed to varying temperatures (∼20–30 °C) while reporting their thermal sensations. In total, for 10 human subjects out of 15, a positive correlation between vision-based indicators, skin temperature, and thermal sensations were observed demonstrating promising potential in inferring thermal sensations of occupants with sufficient sensitivity 

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5. Impact of human body shape on free convection heat transfer

   https://doi.org/10.1371/journal.pone.0318842  

   Viswanathan, Shri H; Joshi, Ankit; Bartels, Lyle; Sadeghi, Kambiz; Vanos, Jennifer K; Rykaczewski, Konrad (February 2025, PLOS ONE)

   Bhowmik, Arka (Ed.)

   Understanding the thermal comfort and safety of diverse populations within indoor settings requires a quantitative understanding of the primary heat exchange pathways between occupants and their surroundings: radiation and free convection. Thus far, however, free convective heat transfer coefficients have only been determined for the average Western adult. To this end, we investigated how variation in body shape impacts free convection heat transfer using an experimentally validated numerical model. The multiphysics model was compared against experiments conducted using the thermal manikin ANDI (Advanced Newton Dynamic Instrument) in a climate-controlled enclosure across five air-to-skin temperature differences ranging from 4.9 to 13.9°C. The difference between measured and simulated heat fluxes for the whole body, and per anatomical region, was typically <5%, occasionally reaching 15–20%, for some body regions due to physical features not modeled in the virtual ANDI model. Using the validated model, we simulated free convection around a family, or diverse group, of virtual manikins representing the 1^stto 99^thpercentile body mass index (BMI) and height variation in the United States adult population. Our results show that the free convection heat transfer coefficient is independent of human sex and height but decreases slightly with increased BMI. However, the variation from the average manikin in the whole body and regional free convection coefficients with BMI was small, not exceeding 8% and 16%, respectively. Furthermore, our regression coefficients and exponents can be derived from the theorical correlation for free turbulent convection from a vertical plate, which also explains the observed independence of the heat transfer coefficient from the manikins’ height. Overall, these findings demonstrate the general applicability of using an average body shape in indoor thermal audits and/or overheating risk assessments to understand thermal comfort and heat stress. The results and valid application of the model support critical insights for human health, productivity, and well-being connected to heat and cooling in buildings. 

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