Smart & Healthy Built Environments
Eustress vs. Distress: Automated Stress Detection in Offices
Stress is recognized by the World Health Organization as the “epidemic of the 21st century”. While there are many reasons for stress, job pressure is the main cause of people’s stress. However, depending on how the workers perceive job stressors, their stress experience can be positive (eustress) or negative (distress).
Distress is what most people refer to when they feel “stressed out”. It usually results in people feeling overwhelmed when the cause of stress is not within their control. On the other hand, eustress motivates individuals to reach their goals, face challenges and achieve success and fulfillment. Differentiating between a positive and negative appraisal of stress is important, as eustress may be one of the most powerful resources to prevent or reduce distress at work and as such lead to a productive and energizing work environment. While extensively studied, stress detection research widely considers all stress-related data as distress. Therefore, the aim of this project attempts to address this significant gap in real-world understanding of distress versus eustress, by creating automated eustress vs distress detection framework using machine learning techniques. The framework will examine facial expressions, physiological signals, and human-computer interactions as potential predictors of eustress vs distress during office work.
Impact of IEQ Factors on Well-being & Performance
The evolving dynamics of our workspaces have necessitated deeper insights into Indoor Environmental Quality (IEQ) and its impact on cognitive functioning and well-being. In our investigation, we explored the main and interaction effects of temperature, noise level, and lighting Correlated Color Temperature (CCT) on various cognitive and comfort parameters.
Our findings illuminated that temperature had a significant moderating influence on the noise level and lighting CCT impact on selective attention. Creativity was influenced by gender and its interaction with the noise level. Acoustic comfort varied significantly with temperature. Additionally, thermal comfort was influenced by the combined moderating effect of lighting CCT and BMI on temperature. Visual comfort was driven by the moderation effect of gender on lighting CCT. Overall comfort was affected by the noise level and temperature. Finally, correlations were observed between cognitive performance indicators and subjective IEQ comfort votes, emphasizing the importance of environmental comfort in elevating or hindering cognitive performance. In a practical context, this research has profound implications for building designers, facility managers, and developers of IEQ systems.
Smart IoT Desk for Well-being and Productivity
Office workers spend most of their working time at their desks, where they are engaged in sedentary behavior, and usually subjected to poor indoor thermal and lighting conditions. Prolonged sitting, and long term exposure to homogeneous temperatures have been linked with reduced metabolism, increased obesity, and increased risk of cardiovascular disease and type two diabetes.
Furthermore, uncomfortable thermal environment and improper lighting conditions have a negative influence on worker productivity and well being. We envision smart desks in the near future to provide a solution to adverse health and productivity impacts that current office work entails. The smart desk uses a wide range of sensors to monitor the environment around the user, as well as the user behavior. The desk uses reinforcement learning to learn and adapt to their thermal, lighting and posture preferences. The desk will control the local thermal and lighting environment around the user based on user preferences while trying to promote health and productivity based on the best practices identified in literature. The goal is to engage users in a bi-directional interaction where the desk promotes exposure to wider range of thermal conditions, and healthier use of sit-stand regimen to improve their productivity and reduce adverse health impacts from the indoor environment.
Health during Work From Home & Impact of IEQ on Well-being & Productivity
To understand impacts of social, behavioral and physical factors on well-being of office workstation users during COVID-19 work from home (WFH) period. A questionnaire was deployed from April 24 to June 11, 2020 and 988 responses were valid. Linear regression, multinomial logistic regression and chi-square tests were used to understand factors associated with overall physical and mental health statuses and number of new physical and mental health issues. Decreased overall physical and mental well-being after WFH were associated with physical exercise, food intake, communication with coworkers, children at home, distractions while work- ing, adjusted work hours, workstation set-up and satisfaction with workspace indoor environmental factors. This study highlights factors that impact workers’ physical and mental health well-being while WFH and provides a foundation for considering how to best support a positive WFH experience. Nose- and throat-related symptoms and skin-related symptoms were only uniquely predicted by low satisfaction with humidity. Low satisfaction with glare uniquely predicted an increase in musculoskeletal discomfort. Symptoms related to mental stress, rumination, or worry were predicted by low satisfaction with air quality and noise. Finally, low satisfaction with noise and indoor temperature predicted the prevalence of symptoms related to trouble concentrating, maintaining attention, or focus. Workers with higher income were more satisfied with humidity, air quality, and indoor temperature and had better overall mental health. Older individuals had increased satisfaction with natural lighting, humidity, air quality, noise, and indoor temperature. Findings from this study can inform future design practices that focus on hybrid home-work environments by highlighting the impact of IEQ factors on occupant well-being.