Enhancing Office Worker Wellness
In the U.S., there are 81 million office workers who spend 75% or more of their day working at a desk. Unfortunately, increased daily sitting time is linked to significant health conditions, including cardiovascular diseases and diabetes. Multiple other health-related issues arise in these workers due to poor ergonomic habits. Health conditions are further exacerbated by building-level control of environmental conditions, most specifically lighting and temperature.
One method of enhancing office worker health is to leverage advances in artificial intelligence to develop an intelligent workstation that can support healthy environmental and behavioral changes either automatically or via an interactive interface. Our transdisciplinary research team envisions the emergence of a genuine partnership and coevolution of workers and their workstations. Specifically, we are working to design an intelligent workstation that learns worker preferences and patterns. We are exploring the ways in which an intelligent workstation and worker can coevolve through an ongoing, bidirectional process of sensing, feedback and learning to adjust postural, thermal and visual conditions at the workstation and moderate poor behaviors.
Several important research challenges will be addressed by our work:
- Machine learning of user preferences, habits and patterns
- Identification of shared objectives and supportive actions
- Establishing machine-human symbiosis to take actions that progress toward best practices (e.g., healthiest)
Watch our video below to learn more about this exciting project:
Coadaptation of Intelligent Office Desks and Human Users to Promote Worker Productivity, Health and Wellness
National Science Foundation - Division of Civil, Mechanical, and Manufacturing Innovation (CMMI)
Co-PIs: Becerik, Roll, Lucas
Award Number: 1763134
Total Funding: $667,716
Funding Period: 8/1/18 - 7/31/22
Rodrigues, P. B., Xiao, Y., Fukumura, Y. E., Awada, M., Aryal, A., Becerik-Gerber, B., Lucas, G., & Roll, S. C. (2022). Ergonomic assessment of office worker postures using 3D automated joint angle assessment. Advanced Engineering Informatics, 52, 101596. https://doi.org/10.1016/j.aei.2022.101596 Show abstract
Sedentary activity and static postures are associated with work-related musculoskeletal disorders (WMSDs) and worker discomfort. Ergonomic evaluation for office workers is commonly performed by experts using tools such as the Rapid Upper Limb Assessment (RULA), but there is limited evidence suggesting sustained compliance with expert’s recommendations. Assessing postural shifts across a day and identifying poor postures would benefit from automation by means of real-time, continuous feedback. Automated postural assessment methods exist; however, they are usually based on ideal conditions that may restrict users’ postures, clothing, and hair styles, or may require unobstructed views of the participants. Using a Microsoft Kinect camera and open-source computer vision algorithms, we propose an automated ergonomic assessment algorithm to monitor office worker postures, the 3D Automated Joint Angle Assessment, 3D-AJA. The validity of the 3D-AJA was tested by comparing algorithm-calculated joint angles to the angles obtained from manual goniometry and the Kinect Software Development Kit (SDK) for 20 participants in an office space. The results of the assessment show that the 3D-AJA has mean absolute errors ranging from 5.6° ± 5.1° to 8.5° ± 8.1° for shoulder flexion, shoulder abduction, and elbow flexion relative to joint angle measurements from goniometry. Additionally, the 3D-AJA showed relatively good performance on the classification of RULA score A using a Random Forest model (micro averages F1-score = 0.759, G-mean = 0.811), even at high levels of occlusion on the subjects’ lower limbs. The results of the study provide a basis for the development of a full-body ergonomic assessment for office workers, which can support personalized behavior change and help office workers to adjust their postures, thus reducing their risks of WMSDs.
Keywords. Ergonomic assessment; RULA; Engineering office environments; Depth camera; Computer vision; Machine learning
Awada, M., Becerik-Gerber, B., Lucas, G., & Roll, S. (2021). Associations among home indoor environmental quality factors and worker health while working from home during COVID-19 pandemic. Journal of Engineering for Sustainable Buildings and Cities, 2(4), 041001. https://doi.org/10.1115/1.4052822 Show abstract
The outbreak of SARS-CoV-2 virus forced office workers to conduct their daily work activities from home over an extended period. Given this unique situation, an opportunity emerged to study the satisfaction of office workers with indoor environmental quality (IEQ) factors of their houses where work activities took place and associate these factors with mental and physical health. We designed and administered a questionnaire that was open for 45 days during the COVID-19 pandemic and received valid data from 988 respondents. The results show that low satisfaction with natural lighting, glare and humidity predicted eye related symptoms, while low satisfaction with noise was a strong predictor of fatigue or tiredness, headaches or migraines, anxiety, and depression or sadness. 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.
Fukumura, Y. E., Schott, J. M., Lucas, G. M., Becerik-Gerber, B., & Roll, S. C. (2021). Negotiating time and space when working from home: Experiences during COVID-19. OTJR: Occupation, Participation and Health, 41(4), 223-231. https://doi.org/10.1177/15394492211033830 Show abstract
Stay-at-home mandates following the COVID-19 pandemic increased work from home (WFH). While WFH offers many benefits, navigating work in nontraditional contexts can be a challenge. The objective of this study was to explore the benefits and challenges of WFH during COVID-19 to identify supports and resources necessary. Comments from two free-response questions on a survey regarding experiences of WFH (N = 648, N = 366) were analyzed using inductive qualitative content analysis. Four themes emerged: time use, considerations of working in the home space, intersections between work-life and home-life, and temporality of WFH as situated within a pandemic. Across all themes were concerns related to participation in both work and home roles, work performance, and well-being. Findings highlight the importance of support during times of disruption of occupational patterns, roles, and routines. Despite challenges, many individuals hoped to continue WFH. Organizations should consider the complex intersections of work-life and home-life to develop supportive policies and resources.
Keywords. work; survey; context; health; occupational balance
Roll, S. ., Lucas, G. M., & Becerik-Gerber, B. (2021). Authors’ response to “Work from home (WFH) during COVID-19: Is virtual reality (VR) a new solution to new problems?”. Journal of Occupational and Environmental Medicine, 63(10), e757-e758. https://doi.org/10.1097/JOM.0000000000002340 Show abstract
Awada, M., Lucas, G., Becerik-Gerber, B., & Roll, S. (2021). Working from home during the COVID-19 pandemic: Impact on office worker productivity and work experience. Work, 69(4), 1171-1189. https://doi.org/10.3233/WOR-210301 Show abstract
Background. With the COVID-19 pandemic, organizations embraced Work From Home (WFH). An important component of transitioning to WFH is the effect on workers, particularly related to their productivity and work experience.
Objectives. The objective of this study is to examine how worker-, workspace-, and work-related factors affected productivity and time spent at a workstation on a typical WFH day during the pandemic.
Methods. An online questionnaire was designed and administered to collect the necessary information. Data from 988 respondents were included in the analyses.
Results. Overall perception of productivity level among workers did not change relative to their in-office productivity before the pandemic. Female, older, and high-income workers were likely to report increased productivity. Productivity was positively influenced by better mental and physical health statuses, having a teenager, increased communication with coworkers and having a dedicated room for work. Number of hours spent at a workstation increased by approximately 1.5 hours during a typical WFH day. Longer hours were reported by individuals who had school age children, owned an office desk or an adjustable chair, and had adjusted their work hours.
Conclusion. The findings highlight key factors for employers and employees to consider for improving the WFH experience.
Fukumura, Y. E., McLaughlin Gray, J., Lucas, G., Becerik-Gerber, B., & Roll, S. C. (2021). Office worker perspective on an artificial intelligence workstation: A qualitative study. American Journal of Occupational Therapy, 75(Supplement_2), 7512505154. https://doi.org/10.5014/ajot.2021.75S2-RP154 Show abstract
Accepted for AOTA INSPIRE 2021 but unable to be presented due to online event limitations.
This study explored office workers' perspectives on including artificial intelligence (AI) in their office workspace. Following an iterative analysis of six focus-group interviews with a total of 45 participants, three constructs emerged. Rich discussions demonstrated how acceptability of an AI workstation is complex and affected by the person, context, and their occupations.
Aryal, A., Becerik-Gerber, B., Lucas, G. M., & Roll, S. C. (2021). Intelligent agents to improve thermal satisfaction by controlling personal comfort systems under different levels of automation. IEEE Internet of Things Journal, 8(8), 7089-7100. https://doi.org/10.1109/JIOT.2020.3038378 Show abstract
Heating, ventilation, and air conditioning (HVAC) systems account for 43% of building energy consumption, yet only 38% of commercial building occupants are satisfied with the thermal environment. The primary reasons for low occupant satisfaction are that HVAC operations do not integrate occupant comfort requirements nor control the thermal environment at the individual level. Personal comfort systems (PCS) enable local control of the thermal environment around each occupant. However, full manual control of PCS can be inefficient, and fully automated PCS reduces an occupant’s perceived control over the environment, which can then lead to lower satisfaction. A better solution might lie somewhere between fully manual and fully automated environmental control. In this paper, we describe the development and implementation of an internet of things (IoT) based intelligent agent that learns individual occupant comfort requirements and controls the thermal environment using PCS (i.e., a local fan and a heater). We tested different levels of automation where control is shared between an intelligent agent and the end user. Our results show that PCS use improves occupant satisfaction and including some level of automation can improve occupant satisfaction further than what is possible with manually operated PCS. Among the levels of automation investigated, Inquisitive Automation, where the user approves/declines the control actions of the intelligent agent before execution, led to highest occupant satisfaction with the thermal environment.
Keywords. building automation, thermal comfort, smart systems, smart buildings, indoor environments
Xiao, Y., Becerik-Gerber, B., Lucas, G., & Roll, S. C. (2021). Impacts of working from home during COVID-19 pandemic on physical and mental well-being of office workstation users. Journal of Occupational and Environmental Medicine, 63(3), 181-190. https://doi.org/10.1097/JOM.0000000000002097 Show abstract
Objective. To understand impacts of social, behavioral and physical factors on well-being of office workstation users during COVID-19 work from home (WFH).
Methods. 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.
Results. Decreased overall physical and mental well-being after WFH were associated with physical exercise, food intake, communication with coworkers, children at home, distractions while working, adjusted work hours, workstation set-up and satisfaction with workspace indoor environmental factors.
Conclusion. 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.
Keywords. COVID-19 pandemic, home office, mental well-being, physical well-being, work from home
Fukumura, Y. E., McLaughlin Gray, J., Lucas, G. M., Becerik-Gerber, B., & Roll, S. C. (2021). Worker perspectives on incorporating artificial intelligence into office workspaces: Implications for the future of office work. International Journal of Environmental Research and Public Health, 1(4), 1690. https://doi.org/10.3390/ijerph18041690 Show abstract
Workplace environments have a significant impact on worker performance, health, and well-being. With machine learning capabilities, artificial intelligence (AI) can be developed to automate individualized adjustments to work environments (e.g., lighting, temperature) and to facilitate healthier worker behaviors (e.g., posture). Worker perspectives on incorporating AI into office workspaces are largely unexplored. Thus, the purpose of this study was to explore office workers’ views on including AI in their office workspace. Six focus group interviews with a total of 45 participants were conducted. Interview questions were designed to generate discussion on benefits, challenges, and pragmatic considerations for incorporating AI into office settings. Sessions were audio-recorded, transcribed, and analyzed using an iterative approach. Two primary constructs emerged. First, participants shared perspectives related to preferences and concerns regarding communication and interactions with the technology. Second, numerous conversations highlighted the dualistic nature of a system that collects large amounts of data; that is, the potential benefits for behavior change to improve health and the pitfalls of trust and privacy. Across both constructs, there was an overarching discussion related to the intersections of AI with the complexity of work performance. Numerous thoughts were shared relative to future AI solutions that could enhance the office workplace. This study’s findings indicate that the acceptability of AI in the workplace is complex and dependent upon the benefits outweighing the potential detriments. Office worker needs are complex and diverse, and AI systems should aim to accommodate individual needs.
Keywords. workspace; office work; computer workstations; artificial intelligence
Aryal, A., Becerik-Gerber, B., Anselmo, F., Roll, S. C., & Lucas, G. (2019). Smart desks to promote comfort, health and productivity in offices: A vision for future workplaces. Frontiers in Built Environment, 5, 76. https://doi.org/10.3389/fbuil.2019.00076 Show abstract
People spend most of their day in buildings, and a large portion of the energy in buildings is used to control the indoor environment for creating acceptable conditions for occupants. However, majority of the building systems are controlled based on a ‘one size fits all’ scheme which cannot account for individual occupant preferences. This leads to discomfort, low satisfaction and negative impacts on occupants’ productivity, health and well-being. In this paper, we describe our vision of how recent advances in Internet of Things (IoT) and machine learning can be used to add intelligence to an office desk to personalize the environment around the user. The smart desk can learn individual user preferences for the indoor environment, personalize the environment based on user preferences, and act as an intelligent support system for improving user comfort, health and productivity. We briefly describe the recent advances made in different domains that can be leveraged to enhance occupant experience in buildings and describe the overall framework for the smart desk. We conclude the paper with a discussion of possible avenues for further research.
Keywords: Personalized environments, Smart desks, IoT (internet of things), Smart buildings, Indoor environment quality (IEQ)
Complete Presentation List
Fukumura, Y. E., Becerik-Gerber, B., Lucas, G. M., & Roll, S. C. (2020). Understanding office worker behavior to Inform an artificial intelligence workstation. Poster presentation at NIH Health in Buildings Roundtable Conference, Virtual Presentation.
Aryal, A., Becerik-Gerber, B., Anselmo, F., Roll, S. C., & Lucas, G. (2018). Smart desk to promote health and productivity. Poster presentation at NIH/NSF/CDC/GSA Health in Buildings for Today and Tomorrow: An Interdisciplinary Conference on Health and the Sustainable Built Environment, Bethesda, MD.