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1. Can Infrared Facial Thermography Disclose Mental Workload in Indoor Thermal Environments?

   https://doi.org/10.1145/3363459.3363528  

   Wang, Xi; Li, Da; Menassa, Carol; Kamat, Vineet. (November 2019, UrbSys'19: Proceedings of the 1st ACM International Workshop on Urban Building Energy Sensing, Controls, Big Data Analysis, and Visualization)

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   Mental workload represents the mental resources an individual devotes to a task. In a building environment, understanding how ambient thermal conditions affect occupants' mental workload offers an opportunity to achieve optimal thermal settings for the heating, ventilation, and air conditioning (HVAC) systems. However, directly measuring mental workload on a large and continuous scale requires occupants to perform subjective tests or wear electroencephalogram (EEG) or similar devices, which is impractical. This paper assesses the feasibility of using infrared facial thermography captured by a low-cost thermal camera to disclose mental workload. An experiment was conducted to measure the facial skin temperature while subjects performed cognitive tasks in three different thermal environments, representing occupants' thermal sensation of slightly cool, neutral, and slightly warm. Mental workload was measured using an EEG headset to eliminate subjective bias. The correlations between facial temperature and mental workload vary with different individuals and thermal conditions. Relatively strong correlations are found in the neutral environment and in the regions of ears, mouth, and neck. The results also suggest that future work should collect data under extended experiment duration. This is because it was observed that the response of facial skin temperature to mental workload varies with task type; thus, increasing the repetitiveness for each type of task or using more challenging tasks in the experiment could potentially lead to more insights on this relationship. 

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2. Investigating the Neurophysiological Effect of Thermal Environment on Individuals' Performance Using Electroencephalogram

   Wang, Xi; Li, Da; Menassa, Carol. C; and Kamat, Vineet R. (January 2019, International Conference on. Computing in Civil Engineering (i3CE): Smart Cities, Sustainability, and Resilience)

   The thermal environment has a great influence on individuals’ performance; however, factors such as one’s motivation to perform well under experimental conditions cause difficulties in assessing how room temperature affect subjects’ performance. One approach to overcome this problem is to understand the changes in individuals’ neurophysiological conditions. This paper reports on the results of an experiment where electroencephalogram (EEG) data were collected from 5 subjects while they performed four computerized cognitive tasks. Power spectral density of EEG signals in three different thermal environments, slightly cool, neutral, and slightly warm, was compared within subjects. In most cases, significant differences in PSD of the frontal theta (4–8 Hz) activity are observed, indicating individuals’ mental effort varies with room temperature. In the long run, the increased mental workload will reduce individuals’ performance and be detrimental to their productivity. The study indicates that the proposed method could be implemented on a larger scale for further studies. 

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3. Do We Overestimate the Impact of Carbon Dioxide on Cognition and Decision-Making?: Preliminary Evidence

   Hurley, Rachel; Belyamani, Mohamed; Djamasbi, Soussan; Somasse, Gbetonmasse; Strauss, Sarah; Liu, Shichao (July 2022, The 5th International Conference on Building Energy & Environment (COBEE))

   The purpose of this study is to investigate the combined impact of mask-wearing on cognitive performance and risk-taking behaviors. Participants were divided into a control group (N=24) without and an experimental group (N=27) with a surgical mask. Both groups completed the tasks in a warm environment (30 oC) where the conditions can reduce cognition and decision-making as well. These conditions are common in indoor spaces without sufficient air conditioning during a heat wave. Cognition and risk-taking behaviors were assessed using computerized tests. Results showed that mask-wearing in warm environment did not negatively impact cognitive performance, nor did it increase risk-taking behavior as the concept of risk compensation predicts, even when the CO2 concentration was elevated to approximately 29,000 ppm on average inside the mask. On the contrary, mask-wearing participants showed less risk-taking behaviors, slightly better response inhibition and better short-term memory. These results do not support previous findings suggesting that even a moderately increased indoor CO2 level can reduce cognition. We hypothesize that human adaptation effects (due to mask-wearing on a daily basis) make people less vulnerable to the adverse environment (i.e., excessive air temperature and CO2 levels), which will be investigated in the future studies. 

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4. Transitions Between Low and High Levels of Mental Workload can Improve Multitasking Performance

   https://doi.org/10.1080/24725838.2020.1770898  

   Devlin, Shannon Patricia; Moacdieh, Nadine Marie; Wickens, Christopher D.; Riggs, Sara Lu (January 2020, IISE Transactions on Occupational Ergonomics and Human Factors)

   Complex and dynamic environments including military operations, healthcare, aviation, and driving require operators to transition seamlessly between levels of mental workload. However, little is known about how the rate of an increase in workload impacts multitasking performance, especially in the context of real-world tasks. We evaluated both gradual and sudden workload increases in the dynamic multitasking environment of an Unmanned Aerial Vehicle (UAV) command and control testbed and compared them to constant workload. Workload transitions were found to improve response time and accuracy compared to when workload was held constant at low or high. These results suggest that workload transitions may allow operators to better regulate mental resources. These findings can also inform the design of operations and technology to assist operators’ management of cognitive resources, which include negating the adverse effects of vigilance decrements during low workload periods and data overload during high workload periods. Background: High workload and workload transitions can affect performance; however, it is not clear how the rate of transition from low to high workload influences performance in a multitasking setting. Purpose: We investigated the effect of workload transition rate on performance in a multitasking environment that is akin to the expectations of operators in complex, data-rich work domains. Method: An Unmanned Aerial Vehicle (UAV) command and control testbed was used to vary workload between low, high, gradually transitioning from low to high, and suddenly transitioning from low to high. Performance measures consisted of the response time and accuracy of one primary task and three secondary tasks. Analyses compared: (a) performance differences between gradual and sudden increases in workload; (b) performance during the low workload phases of the workload transitions; and (c) performance during the high workload phases of the workload transitions. Results: Overall, there were limited performance differences between gradual and sudden workload transitions. However, both types of transitions led to better performance than constant workload, lending some support for the effort regulation explanation which suggests that participants actively evaluated the amount of mental resources necessary to successfully complete a task after a workload transition. Conclusions: Gradual and sudden workload transitions benefit primary and secondary task performance, suggesting that the applicability of existing theoretical explanations depend on the context. For example, varying task demands can be a means to assist operators in the appropriate regulation of mental resources in domains with interdependent tasks. These findings can inform occupation and technology design to support task management. 

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5. Thermal and RGB-D Sensor Fusion for Non-Intrusive Human Thermal Comfort Assessment

   Li, Da; Menassa, Carol. C; and Kamat, Vineet R. (January 2019, CIB World Building Congress 2019, Hong Kong)

   It is well established that thermal comfort is an influential factor in human health and wellbeing. Uncomfortable thermal environments can reduce occupants’ comfort and productivity, and cause symptoms of sick building syndrome. To harness the built environment as a medium to support human health, well-being, and engagement, it is significantly important to understand occupants’ thermal comfort in real time. To this end, this study proposes a non-intrusive method to collect occupants’ facial skin temperature and interpret their thermal comfort conditions by fusing the thermal and RGB-D images collected from multiple low-cost thermographic and Kinect sensors. This study distinguishes from existing methods of thermal comfort assessment in three ways: 1) it is a truly non-intrusive data collection approach which has a minimal interruption or participation of building occupants; 2) the proposed approach can simultaneously identify and interpret multiple occupants’ thermal comfort; 3) it uses low-cost thermographic and RGB-D cameras which can be rapidly deployed and reconfigured to adapt to various settings. This approach was experimentally evaluated in a transient heating environment (room temperature increased from 23 to 27 °C) to verify its applicability in real operational built environments. In total, all 6 subjects observed moderate to strong positive correlations between the ambient room temperature and subjects’ facial skin temperature collected using the proposed approach. Additionally, all 6 subjects have voted different thermal sensations at the beginning (the first 5 minutes) and at the end (the last 5 minutes) of the heating experiment, which can be reflected by the significant differences in the mean skin temperature of these two periods (p < .001). Results of this pilot study demonstrate the feasibility of applying the proposed non-intrusive approach to real multi-occupancy environments to dynamically interpret occupants’ thermal comfort and optimize the operation of building heating, ventilation and air conditioning (HVAC) systems. 

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