Gale M. Lucas PhD

Demolition is among the most complex and hazardous sectors of construction, where workers need to work in rapidly changing and cluttered environments. Teleoperation offers a promising approach to reducing operators’ exposure to on-site hazards by enabling remote control of demolition robots, yet existing interfaces are often insufficiently grounded in operators’ needs or validated through real-world testing. This paper presents a sensory-enhanced teleoperation workstation prototype that operationalizes operators’ sensory needs identified in prior studies. The prototype translates these needs into multimodal sensing channels, associated data-flow structures, and corresponding workstation features. It provides a platform for subsequent studies to understand how operators engage with sensory information in real-world scenarios. The prototype also holds the potential to inform operator training and teleoperation research for other demolition machines and related contexts.

Objective. To explore how hybrid workspaces (home vs. office) affect productivity and well-being, and whether indoor environmental quality (IEQ) mediates these associations.

Methods. Nineteen office workers were followed for four months, contributing 4,559 ecological momentary assessments (EMAs) of productivity, mood, stress, and eustress-distress appraisal. Continuous IEQ monitoring captured CO₂, TVOCs, PM₂.₅, temperature, humidity, and noise. Mixed-effects and multilevel mediation models assessed within-person associations.

Results. Office work was associated with higher productivity and greater eustress-distress coexistence, while home work was associated with higher boredom. Mood differences were small, and stress was modestly lower at home. Home workspaces showed poorer air quality. CO₂ and TVOCs were indirectly associated with mood and stress differences.

Conclusions. Hybrid work outcomes differ by location and are partly explained by IEQ, suggesting residential air quality as an occupational health intervention target.

As teleoperated robots become more common on construction sites, human-robot interfaces must better support operators’ sensory needs. This paper presents results from a pilot study comparing a proposed sensory-enhanced teleoperation interface for compact demolition robots with a standard teleoperation interface. Recommendations from demolition stakeholders informed the design of the sensory-enhanced interface, while the standard interface was based on commercially available teleoperated construction equipment. The goal of this study was to refine the sensory-enhanced interface based on user feedback. Ten construction workers tested the interfaces, and we measured their perceived usability, telepresence, and trust in technology.

This study examines environmental comfort differences between home and office workspaces and their associations with productivity and well-being among 19 knowledge workers monitored over four months via ecological momentary assessments. Participants rated comfort across four domains (lighting, temperature, air quality, noise) and reported productivity, mood, stress, and stress states four times daily. Mixed-effects models indicated domain-specific patterns: offices showed higher comfort for lighting (OR=0.56) and noise (OR=0.48), while temperature showed individual heterogeneity. Lighting and temperature comfort were positively associated with productivity (4.3% and 2.4% increase per comfort level), while comfort showed weak associations with mood and stress. Bayesian multinomial models suggested that higher comfort was associated with lower odds of boredom (ORs=0.40-0.56). Substantial between-person heterogeneity was observed in the direction and magnitude of home-office differences in comfort, well-being, and productivity, suggesting that hybrid policies may not be one-size-fits-all and may benefit from greater flexibility, though these findings should be interpreted as exploratory.

Symptoms such as fatigue, headache, low motivation, and difficulty concentrating affect office workers’ cognitive and overall well-being. This study investigates the dynamic relationships among temporal patterns, indoor environmental quality (IEQ) factors, and cognitive symptoms in real offices. We collected about four months of continuous environmental data and ecological momentary assessments (EMAs) from ten office workers and integrated XGBoost and SHAP analysis to identify those relationships. Model performance varied by symptom and participant. Under random train-test splitting, accuracy generally exceeded 70% with F1 scores ranging from 40% to 80%. Performance declined under a temporal split, highlighting the real-world challenge of predicting future symptom states from past observations. Based on SHAP analysis, hour of day and day of week emerged as significant predictors, revealing temporal patterns in cognitive symptoms. Within observed one-hour windows prior to reported symptoms, higher relative humidity was generally associated with increased risk of cognitive symptoms, while higher illuminance was associated with reduced symptom risk. Associations with sound pressure level and TVOCs varied across participants, with no consistent directions. Our data-driven approach provides insights into temporal factors and environmental exposures associated with cognitive symptoms using naturalistic data. These findings highlight the combined influence of temporal and IEQ factors on cognitive symptoms and contribute to the development of adaptive, user-centric workplaces that support cognitive well-being management.

Keywords. Office worker, Cognitive symptoms, Well-being, Machine learning, Longitudinal data, Temporal patterns, Indoor environmental quality

As hybrid work gains traction, understanding exposure to varying indoor environmental quality (IEQ) attributes becomes increasingly important for promoting health, productivity, and equity in workplace models. This longitudinal study investigated key IEQ attributes—temperature, relative humidity (RH), carbon dioxide (CO₂), particulate matter (PM₂.₅), total volatile organic compounds (TVOC), and ambient noise—across 12 participants’ home and office workspaces. Data were collected over 4 months through continuous monitoring and ecological momentary assessments (EMAs). Results revealed significant differences in IEQ variability between the two workspace types. Office workspaces generally maintained more stable conditions due to advanced climate control systems, while home workspaces exhibited greater fluctuations likely influenced by weather, building design, and occupant behaviors. Notably, TVOC and PM₂.₅ levels occasionally exceeded recommended thresholds in some home workspaces, underscoring potential health risks. These findings highlight the need for adaptive strategies, such as improved ventilation, air purification, and occupant education, to enhance IEQ in hybrid workspaces.

Tags. Building design, Control systems, Health hazards, Human and behavioral factors, Hybrid methods, Volatile organic compounds, Work zones

Background. Indoor environmental quality (IEQ) significantly influences occupant stress in office settings, yet the combined effects of multiple environmental stressors, moderated by personal characteristics, remain underexplored.

Objective. This study examines the interaction effects of air temperature, lighting correlated colour temperature (CCT), and background noise on stress responses among office workers, with attention to individual differences in gender and body mass index (BMI).

Methods. A mixed-design controlled experiment was conducted with 52 young adults in an open plan office within a North American Mediterranean climate, varying temperature (20°C vs. 25°C), CCT (2700 K vs. 6500 K), and noise level (50 dB vs. 65 dB). Stress was assessed using physiological and psychological indicators.

Key Results. Stress responses were shaped not by individual environmental attributes in isolation, but through complex interactions among temperature, CCT, and noise, further moderated by BMI and gender. Individuals with overweight/obese BMI showed heightened sensitivity to warm temperatures, cool CCT, and high noise, while males exhibited greater sympathetic activation under warm and noisy conditions compared to females.

Implications. These findings underscore that a one-size-fits-all approach to office environmental design is insufficient. Accounting for occupant heterogeneity, particularly BMI and gender, is essential for developing personalized IEQ strategies that promote workplace well-being.

Keywords. health, heart rate variability, indoor environmental quality, interaction effect, stress

Despite the benefits of remotely operated compact demolition machines in constrained and hazardous environments, many safety and occupational risks remain. Operators often stay close to the machines, exposing themselves to the risks of structural collapses, falling debris, dust, and noise. In this study, we employed a generative user experience (UX) framework with six demolition industry professionals to inform the design considerations for a sensory-enhanced teleoperation interface for demolition robots. Through narrative interviews and focus groups, we identified demolition operators’ sensory needs during traditional demolition tasks involving manned and remotely operated machines and explored potential sensory features for a teleoperation interface for demolition robots. To increase the trustworthiness of the findings, we subsequently conducted a verification strategy where over 60 demolition stakeholders tested and provided feedback on the proposed teleoperation interface features within a virtual environment. Findings indicate that demolition operators use multiple sensory channels to perceive and interact with the environment during traditional demolition tasks. However, certain site conditions (e.g., noise, constrained spaces, clutter) still compromise their performance, safety, and well-being. Multimodal, simple, safe, and personalizable teleoperation interfaces that provide appropriate levels of control over the robots are preferred. Key suggestions included improvements in the robot’s controllers and the inclusion of mechanisms to facilitate communications with on-site workers and the perception of hazards. The findings inform the design considerations for a sensory-enhanced teleoperation interface for compact demolition robots. Additionally, the proposed generative UX framework can be applied to other construction applications to facilitate identifying operators’ needs and designing teleoperation interfaces

In modern workplaces, the well-being and productivity of employees are increasingly recognized as essential for organizational success. This study explores the impact of lighting interventions—specifically, Correlated Color Temperature (CCT) and illumination intensity—on stress and cognitive function restoration among office workers. A between-subjects experimental design involving 100 participants assessed the effects of various lighting conditions on stress responses and cognitive performance after exposure to stress-inducing and cognitive fatigue tasks. Five experimental conditions were studied: 100 lux & 7000 K, 100 lux & 3000 K, 1000 lux & 7000 K, 1000 lux & 3000 K, and a baseline condition of 500 lux at 3700 K. Results indicated that lighting conditions significantly influence both physiological stress markers (such as skin conductance level and heart rate) and cognitive performance. Specifically, warm, and dimmed lighting (3000 K, 100 lux) effectively reduced stress markers and perceived stress levels, aligning with theories suggesting the calming effects of warmer white light tones. Conversely, cooler lighting (7000 K) was associated with enhanced cognitive performance and reduced cognitive fatigue, potentially due to its similarity to natural daylight, stimulating an alert state conducive to mental tasks. These findings suggest that lighting interventions offer a non-intrusive strategy to improve well-being and productivity in office environments, particularly addressing acute symptoms.

Teleoperation is receiving intense attention due to its potential to address health and safety concerns for construction workers caused by on-site hazards. It allows operators to control robots from a distance outside their field of view using wireless communication technologies. Currently one of the most frequently deployed robotic technologies in construction is the remotely operated demolition robot within the field of view. While distance teleoperation offers great potential for enhancing worker safety and addressing labor shortages, the complex and dynamic demolition sites present unique challenges. This paper introduces the preliminary results of a study that explored potential challenges in demolition robot teleoperation, informed by the challenges identified in traditional demolition machine operations and the key concerns raised by industry professionals. A user-centered approach was employed through narrative interviews and focus groups with demolition professionals. The findings indicate that the challenges faced in traditional demolition machine operations may persist in teleoperation and could be further exacerbated by the sensory degradation inherent in teleoperation. Besides, the interactions among challenges increase the complexity of their overall impact. Moreover, enhancing operators’ situational awareness without inducing cognitive overload or distraction is critical for effectively addressing these challenges. Additionally, the results suggest the need for context-aware, multimodal teleoperation interfaces to assist operators in managing operational challenges. This study contributes to understanding challenges that operators may face during teleoperation, offering valuable insights for developing teleoperation interfaces adaptable to diverse demolition contexts.

Keywords. Challenges, Demolition, Teleoperation

The noise produced in demolition sites can mask safety-critical sounds that inform operators about task conditions and hazards. These problems are exacerbated in teleoperated demolition, where the separation between operator and site compromises operators' situation awareness and cognitive loads. This paper assessed the effects of environmental sounds with and without attenuation on the operators' performance and response (e.g., stress, attention, task engagement) during teleoperated demolition. Eighty participants completed three virtual demolition tasks under different environmental sound conditions, i.e., no sound (NS), unfiltered sound (US), and filtered sound (FS) with 20-dB attenuation of background noise and robot's sounds to allow focus on safety and task conditions. The results show that US induced more stress than NS and FS. Also, FS resulted in fewer collisions, faster reaction times, and greater attention and task engagement than US. These results can support the design of sound feedback interfaces for teleoperation in construction.

Keywords. Demolition, Electrodermal activity, Environmental sound, Heart rate variability, Performance, Robot, Safety, Stress, Teleoperation

With the exponential rise in the prevalence of automation, trust in such technology has become more critical than ever before. Trust is confidence in a particular entity, especially in regard to the consequences they can have for the trustor, and calibrated trust is the extent to which the judgments of trust are accurate. The focus of this paper is to reevaluate the general understanding of calibrating trust in automation, update this understanding, and apply it to worker’s trust in automation in the workplace. Seminal models of trust in automation were designed for automation that was already common in workforces, where the machine’s “intelligence” (i.e., capacity for decision making, cognition, and/or understanding) was limited. Now, burgeoning automation with more human-like intelligence is intended to be more interactive with workers, serving in roles such as decision aid, assistant, or collaborative coworker. Thus, we revise “calibrated trust in automation” to include more intelligent automated systems.

Keywords. trust, automation, calibrated trust, workers

Stress experiences can have dire consequences for worker performance and well-being, and the social environment of the workplace is a key contributor to worker experience. This study investigated the relationship between hybrid workers’ self-ratings of productivity, mood, and stress with perceptions of positive (eustress) and negative (distress) stress states. We hypothesized that self-ratings would vary across combinations of eustress and distress experiences and that these differences would differ based on the social context. Ecological momentary assessments (EMA) were used to obtain ecologically valid data at four data points each workday across a 4-month study period in a cohort of seven office workers. Findings aligned with the Yerkes–Dodson law, such that higher states of arousal were associated with greater self-perceived productivity, and higher stress magnitudes were found when distress existed. Compared to other states, eustress was associated with higher productivity in work-related activities and better mood across all activity types.

Previous studies have solely focused on establishing Machine Learning (ML) models for automated detection of stress arousal. However, these studies do not recognize stress appraisal and presume stress is a negative mental state. Yet, stress can be classified according to its influence on individuals; the way people perceive a stressor determines whether the stress reaction is considered as eustress (positive stress) or distress (negative stress). Thus, this study aims to assess the potential of using an ML approach to determine stress appraisal and identify eustress and distress instances using physiological and behavioral features. The results indicate that distress leads to higher perceived stress arousal compared to eustress. An XGBoost model that combined physiological and behavioral features using a 30 second time window had 83.38% and 78.79% F₁-scores for predicting eustress and distress, respectively. Gender-based models resulted in an average increase of 2-4% in eustress and distress prediction accuracy. Finally, a model to predict the simultaneous assessment of eustress and distress, distinguishing between pure eustress, pure distress, eustress-distress coexistence, and the absence of stress achieved a moderate F₁-score of 65.12%. The results of this study lay the foundation for work management interventions to maximize eustress and minimize distress in the workplace.

Teleoperated robots are increasingly being used in construction sites, but there is still a need for better human-robot interfaces. Auditory feedback using sonification has commonly been used to complement visual feedback in teleoperation applications. However, it is not yet well understood how operational and environmental sounds can support operators in complex tasks such as construction machine operations. In this paper, we describe the development of a virtual environment to assess the impacts of operational and environmental sounds on operators’ performances and cognitive loads during teleoperated demolition. Our goal is to examine whether different levels of operational and environmental sounds can increase the workers’ situation awareness, operational efficiency, and safety performance. Alternatively, we anticipate that some environmental noises may negatively affect the operators’ performances by increasing their mental workload and stress levels. Consequently, we plan to evaluate the effectiveness of including audio filters that minimize unwanted sounds while prioritizing desired sounds.

Previous studies have primarily focused on predicting stress arousal, encompassing physiological, behavioral, and psychological responses to stressors, while neglecting the examination of stress appraisal. Stress appraisal involves the cognitive evaluation of a situation as stressful or non-stressful, and as a threat/pressure or a challenge/opportunity. In this study, we investigated several research questions related to the association between states of stress appraisal (i.e., boredom, eustress, coexisting eustress-distress, distress) and various factors such as stress levels, mood, productivity, physiological and behavioral responses, as well as the most effective ML algorithms and data signals for predicting stress appraisal. The results support the Yerkes-Dodson law, showing that a moderate stress level is associated with increased productivity and positive mood, while low and high levels of stress are related to decreased productivity and negative mood, with distress overpowering eustress when they coexist. Changes in stress appraisal relative to physiological and behavioral features were examined through the lenses of stress arousal, activity engagement, and performance. An XGBOOST model achieved the best prediction accuracies of stress appraisal, reaching 82.78% when combining physiological and behavioral features and 79.55% using only the physiological dataset. The small accuracy difference of 3% indicates that physiological data alone may be adequate to accurately predict stress appraisal, and the feature importance results identified electrodermal activity, skin temperature, and blood volume pulse as the most useful physiologic features. Implementing these models within work environments can serve as a foundation for designing workplace policies, practices, and stress management strategies that prioritize the promotion of eustress while reducing distress and boredom. Such efforts can foster a supportive work environment to enhance employee well-being and productivity.

This research pioneers the application of a machine learning framework to predict the perceived productivity of office workers using physiological, behavioral, and psychological features. Two approaches were compared: the baseline model, predicting productivity based on physiological and behavioral characteristics, and the extended model, incorporating predictions of psychological states such as stress, eustress, distress, and mood. Various machine learning models were utilized and compared to assess their predictive accuracy for psychological states and productivity, with XGBoost emerging as the top performer. The extended model outperformed the baseline model, achieving an R² of 0.60 and a lower MAE of 10.52, compared to the baseline model’s R² of 0.48 and MAE of 16.62. The extended model’s feature importance analysis revealed valuable insights into the key predictors of productivity, shedding light on the role of psychological states in the prediction process. Notably, mood and eustress emerged as significant predictors of productivity. Physiological and behavioral features, including skin temperature, electrodermal activity, facial movements, and wrist acceleration, were also identified. Lastly, a comparative analysis revealed that wearable devices (Empatica E4 and H10 Polar) outperformed workstation addons (Kinect camera and computer-usage monitoring application) in predicting productivity, emphasizing the potential utility of wearable devices as an independent tool for assessment of productivity. Implementing the model within smart workstations allows for adaptable environments that boost productivity and overall well-being among office workers.

Keywords. productivity; stress; mood; eustress; distress; psychological state; physiological features; behavioral features

We investigated the physiological (heart rate variability) and psychological (state of anxiety, pleasantness, and comfort) effects of ambient bergamot scent on the stress levels of office workers by exposing them to the scent while stressors persisted as the workers continued to work on the office tasks. Forty-eight young adults were randomly assigned to either a control or scent group. Our results show that the stress restoration effect of bergamot scent depends on gender. The change in heart rate variability revealed that bergamot scent increased stress among males but not for females. The reported pleasantness and comfort followed the same trend. Compared to the control groups, females in the scent group thought the office smelled pleasant and felt more comfortable, but males in the scent group reported the opposite. However, no gender effect was found in the level of state anxiety. Specifically, compared to the control groups, both males and females exposed to the bergamot scent self-reported decreasing stress levels. This inconsistency between self-reported stress and physiological measurements is not uncommon, especially among males who are socialized to downplay emotional experiences. Our data suggest that there is indeed a gender difference in the effectiveness of the bergamot scent for reducing stress in office workers.

While Indoor Environmental Quality (IEQ) factors in an environment co-exist, the interaction effects of these factors and their impacts on cognitive functioning and perceived comfort have not been comprehensively examined. In this study, the interaction effects between temperature, lighting Correlated Color Temperature (CCT), and noise levels on selective attention, sustained attention, creativity, acoustics, thermal, visual, and overall IEQ comfort of young adults in open-plan offices in North American Mediterranean climate were presented. In a mixed-design controlled experimental setting, 52 young adults were recruited, and their objective cognitive performance and subjective comfort were assessed through statistical analysis. The experimental set points included [20 °C, 25 °C], [2700 K, 6500 K], and [50 dB, 65 dB] for temperature, lighting color, and noise, respectively. Additionally, the work took into consideration the gender and Body Mass Index (BMI) of participants. The results show that temperature moderated the effect of noise level and lighting CCT on selective attention, while no effect of IEQ factors on sustained attention was found. Creativity was influenced by gender and its interaction with the noise level. Concerning perceived comfort, acoustic comfort varied significantly with temperature. Thermal comfort was influenced by the combined moderating effect of lighting CCT and BMI on temperature, while visual comfort was driven by the moderation effect of gender on lighting CCT. Overall comfort was affected by the noise level and temperature. Finally, cognitive performance indicators were correlated with perceived IEQ comfort votes. Based on the findings of this study, considerations of interactions between noise, lighting CCT, temperature, gender, and BMI can shape occupant-centric priorities for enhanced cognitive functioning and comfort.

We regularly face stress during our everyday activities, to the extent that stress is recognized by the World Health Organization as the epidemic of the 21st century. Stress is how humans respond physically and psychologically to adjustments, experiences, conditions, and circumstances in their lives. While there are many reasons for stress, work and job pressure remain the main cause. Thus, companies are increasingly interested in creating healthier, more comfortable, and stress-free offices for their workers. The indoor environment can induce environmental stress when it cannot satisfy the individual needs for health and comfort. In fact, office environmental conditions (e.g., thermal, and indoor air conditions, lighting, and noise) and interior design parameters (e.g., office layout, colors, furniture, access to views, distance to window, personal control and biophilic design) have been found to affect office workers' stress levels. A line of research based on the stress recovery theory offers new insights for establishing offices that limit environmental stress and help with work stress recovery. To that end, this paper answers ten questions that explore the relation between the indoor office-built environment and stress levels among workers. The answers to the ten questions are based on an extensive literature review to draw conclusions from what has been achieved to date. Thus, this study presents a foundation for future environmental stress related research in offices.

Keywords. Stress; Indoor environmental quality; Stress recovery; Office; Interior design

Human-Building Interaction (HBI) is a convergent field that represents the growing complexities of the dynamic interplay between human experience and intelligence within built environments. This paper provides core definitions, research dimensions, and an overall vision for the future of HBI as developed through consensus among 25 interdisciplinary experts in a series of facilitated workshops. Three primary areas contribute to and require attention in HBI research: humans (human experiences, performance, and well-being), buildings (building design and operations), and technologies (sensing, inference, and awareness). Three critical interdisciplinary research domains intersect these areas: control systems and decision making, trust and collaboration, and modeling and simulation. Finally, at the core, it is vital for HBI research to center on and support equity, privacy, and sustainability. Compelling research questions are posed for each primary area, research domain, and core principle. State-of-the-art methods used in HBI studies are discussed, and examples of original research are offered to illustrate opportunities for the advancement of HBI research.

Keywords. Civil engineering; Environmental impact; Mechanical engineering; Occupational health; Quality of life

This paper seeks to address ten questions that explore the burgeoning field of Human-Building Interaction (HBI), an interdisciplinary field that represents the next frontier in convergent research and innovation to enable the dynamic interplay of human and building interactional intelligence. The field of HBI builds on several existing efforts in historically separate research fields/communities and aims to understand how buildings affect human outcomes and experiences, as well as how humans interact with, adapt to, and affect the built environment and its systems, to support buildings that can learn, enable adaptation, and evolve at different scales to improve the quality-of-life of its users while optimizing resource usage and service availability. Questions were developed by a diverse group of researchers with backgrounds in design, engineering, computer science, social science, and health science. Answers to these questions draw conclusions from what has been achieved to date as reported in the available literature and establish a foundation for future HBI research. This paper aims to encourage interdisciplinary collaborations in HBI research to change the way people interact with and perceive technology within the context of buildings and inform the design, construction, and operation of next-generation, intelligent built environments. In doing so, HBI research can realize a myriad of benefits for human users, including improved productivity, health, cognition, convenience, and comfort, all of which are essential to societal well-being.

Keywords. Building lifecycle; Human-centered; Occupants; Built environment; Well-being; Interaction; Quality of life

Noise is often considered a distractor; however recent studies suggest that sub-attentive individuals or individuals diagnosed with attention deficit hyperactivity disorder can benefit from white noise to enhance their cognitive performance. Research regarding the effect of white noise on neurotypical adults presents mixed results, thus the implications of white noise on the neurotypical population remain unclear. Thus, this study investigates the effect of 2 white noise conditions, white noise level at 45 dB and white noise level at 65 dB, on the cognitive performance, creativity, and stress levels of neurotypical young adults in a private office space. These conditions are compared to a baseline condition where participants are exposed to the office ambient noise. Our findings showed that the white noise level at 45 dB resulted in better cognitive performance in terms of sustained attention, accuracy, and speed of performance as well as enhanced creativity and lower stress levels. On the other hand, the 65 dB white noise condition led to improved working memory but higher stress levels, which leads to the conclusion that different tasks might require different noise levels for optimal performance. These results lay the foundation for the integration of white noise into office workspaces as a tool to enhance office workers’ performance.

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

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.

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

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.

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.

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

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

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

Science fiction has long predicted that technology will develop relationships and interact with humans using emotions, just like other humans do. Technologies that can use emotions in conversations with people are now becoming reality. To do so, technology needs to sense and respond to human emotions and intentions. First, technology should be capable of perception – to understand signals given by the human user, including words, quality of speech and accompanying nonverbal cues such as facial expressions, gestures and posture. The agent would then need to be able to reason about these cues and in relation to its own goals and the users. Finally, the technology needs to be able to translate its resulting decisions into suitable and emotionally rich behaviors. The chapter reviews work on each of these steps in turn: progress toward technology being able to perceive human emotional cues, reason about emotion and generate emotional cues. Finally, we discuss relevant applications for entertainment, education, health and communication.

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)