Evidence to design 'just right' work using active workstations is currently limited

Active time at work following the introduction of a standing and a cycling workstation into worker's office space

Objectives. Active workstations have been proposed to counteract sedentary behavior at work. This study describes office workers' use of and perceptions toward standing and cycling workstations, and assesses whether the two active workstations were sufficient to break sitting time and replace it with 2-4 h of light activity per workday. Methods. This mixed-method study utilized video recording, semi-structured interviews and a questionnaire. The quantitative data covered time spent sitting, standing and on a cycling workstation. The qualitative data were analyzed based on preferences, barriers and facilitators. Results. Participants (n = 15) used active workstations 125.3 (74.5) min/day and spent 79.0 (63.6) min/day using standing versus 46.3 (47.6) min/day using cycling workstations (p = 0.153, d = 0.58). Following the interviews, the standing workstation was preferred over cycling. The ergonomics of the cycling workstation were not optimal and caused discomfort in use. Seven participants broke their sitting time and accumulated 2+ h of light physical activity per workday. Those participants meeting recommendations were older, had a higher body fat percentage and engaged in less physical activity per week. Conclusion. With a preference for standing workstations, our results showed that 47% of workers used standing and cycling workstations to accumulate 2+ h of active time per day.

Knee Extension Exercise Effects on Physiological and Psychophysical Performance: Normal Weight Versus Obese Office Workers

BACKGROUND

Knee extension exercise is useful and practical for obese and overweight people as this form of exercise is effective in minimizing body weight loading on joints and improving the body's physiological function. This study aimed to compare the physiological and psychophysical parameters of office workers while computer-based working in an active workstation equipped with an active footrest (AFR) prototype with a mechanism for performing knee extension exercises in a sitting position, and also to compare the physiological and psychophysical parameters among normal-weight and obese office workers.

METHODS

In this quasi-experimental study, the physiological parameters of heart rate (HR) and energy expenditure (EE) (measured with the Fitbit Charge HR smartwatch) were measured in two cross-over random sessions for 32 office workers (16 normal-weight and 16 obese) aged 28 to 50 years (M = 42.72, standard deviation [SD] = 4.37) while performing office tasks in sitting and active workstations (equipped with AFR). Perceived physical exertion, comfort, fatigue, and liking were also measured by rating the participants.

FINDINGS

Short-term activity of the participants with AFR performing computer tasks significantly improved physiological and psychophysical parameters compared with the participants in sitting workstations. However, there was no significant difference in the effect of AFR on physiological and psychophysical parameters between normal-weight and obese participants.

CONCLUSIONS/APPLICATION TO PRACTICE

Given the significant increase in EE and HR resulting from exercise with AFR compared with the conventional workstation, the use of AFR can help office workers achieve the minimum standard of physical activity at their workplace.

Implementing Machine Learning Algorithms to Classify Postures and Forecast Motions When Using a Dynamic Chair

Many modern jobs require long periods of sitting on a chair that may result in serious health complications. Dynamic chairs are proposed as alternatives to the traditional sitting chairs; however, previous studies have suggested that most users are not aware of their postures and do not take advantage of the increased range of motion offered by the dynamic chairs. Building a system that identifies users’ postures in real time, as well as forecasts the next few postures, can bring awareness to the sitting behavior of each user. In this study, machine learning algorithms have been implemented to automatically classify users’ postures and forecast their next motions. The random forest, gradient decision tree, and support vector machine algorithms were used to classify postures. The evaluation of the trained classifiers indicated that they could successfully identify users’ postures with an accuracy above 90%. The algorithm can provide users with an accurate report of their sitting habits. A 1D-convolutional-LSTM network has also been implemented to forecast users’ future postures based on their previous motions, the model can forecast a user’s motions with high accuracy (97%). The ability of the algorithm to forecast future postures could be used to suggest alternative postures as needed.

Designing and Usability testing of a New Prototype Active Footrest for Knee Extension Exercise Among Office Workers

OBJECTIVES

The active factor along with light exercise can reduce static muscle work and increase muscle flexibility and endurance. Accordingly, this study aimed to design and prototype a new active footrest, implemented in conventional sitting workstations and to test its usability among office workers.

METHODS

The steps taken to design and prototype the active footrest were a) selection of an exercise appropriate for goals of ergonomic interventions, b) idea development, c) selection of the best conceptual design, d) design with SOLIDWORKS version 2016 software, and e) fabrication of a prototype. Afterward, the usability of the active footrest prototype was assessed among 20 office workers (10 females) using field data by the System Usability Scale.

RESULTS

Upon the completion of the design steps, the active footrest prototype was prototyped by taking into account design criteria (e.g. functionality, inclusive design, easy application, and reduction of additional body movement), anthropometric data and mechanical properties. The participants rated the usability of the active workstation as 89 ± 8.21 (out of 100) and indicating good usability results.

CONCLUSION

In this study, an active footrest was designed and prototyped to perform knee extension exercise with the capability of being implemented in conventional sitting workstations.

Standing Desks in a Grade 4 Classroom over the Full School Year

School-aged children are spending increasingly long periods of time engaged in sedentary activities such as sitting. Recent school-based studies have examined the intervention effects of introducing standing desks into the classroom in the short and medium term. The aim of this repeated-measures crossover design study was to assess the sit-stand behaviour, waking sedentary time and physical activity, and musculoskeletal discomfort at the start and the end of a full school year following the provision of standing desks into a Grade 4 classroom. Accelerometry and musculoskeletal discomfort were measured in both standing and traditional desk conditions at the start and at the end of the school year. At both time points, when students used a standing desk, there was an increase in standing time (17–26 min/school day) and a reduction in sitting time (17–40 min/school day). There was no significant difference in sit-stand behaviour during school hours or sedentary time and physical activity during waking hours between the start and the end of the school year. Students were less likely to report discomfort in the neck and shoulders when using a standing desk and this finding was consistent over the full school year. The beneficial effects of using a standing desk were maintained over the full school year, after the novelty of using a standing desk had worn off.