Stability of activity space footprint, size, and environmental features over six months

How many days of indoor positioning system data are required to characterise typical movement behaviours of office workers?

Indoor Positioning Systems (IPS) appear to offer great potential to study the movement and interaction of people and their working environment, including office workplaces. But little is known about appropriate durations for data collection. In this study, location observations collected from 24 office workers on a 1220 m² office floor over a 3-month period, were analysed to determine how many days are required to estimate their typical movement and spatial behaviours. The analysis showed that up to 8 days of data was sufficient to characterise participants' typical daily movement behaviours and 10 days were required to estimate their typical spatial mobility. However, the results also indicate that 5 weeks of data collection are required to gather the necessary 10 days of data from each participant. These findings will help researchers and workplace professionals to understand the capabilities and requirements of IPS when considering their use in indoor work environments.

Stop motion: using high resolution spatiotemporal data to estimate and locate stationary and movement behaviour in an office workplace

Prolonged periods of stationary behaviour, a common occurrence in many office workplaces, are linked with a range of physical disorders. Investigating the physical context of this behaviour may be a key to developing effective interventions. This study aimed to estimate and locate the stationary and movement behaviours of office workers (n = 10) by segmenting spatiotemporal data collected over 5 days in an office work-based setting. The segmentation method achieved a balanced accuracy ≥85.5% for observation classification and ≥90% for bout classification when compared to reference data. The results show the workers spent the majority of their time stationary (Mean = 86.4%) and had on average, 28.4 stationary and 25.9 moving bouts per hour. While these findings accord with other studies, the segmented data was also visualised, revealing that the workers were stationary for periods ≥5 min at multiple locations and these locations changed across time. Practitioner Summary: This study applied a data segmentation method to classify stationary and moving behaviours from spatiotemporal data collected in an office workplace. The segmented data revealed not only what behaviours occurred but also their location, duration, and time. Segmenting spatiotemporal data may add valuable physical context to aid workplace research.

Activity space, office space: Measuring the spatial movement of office workers

A key to the development of more effective interventions to promote movement and reduce physical inactivity in office workplaces may be to measure and locate individual's spatial movement. Using an activity space estimation method, high resolution location data collected from 15 office workers over 12 days were used to estimate and analyse the location and extent of their daily spatial movement whilst in an office work-based setting. The results indicated that the method, kernel density estimation, combined with location data offers significant opportunities to not only measure and compare spatial movement behaviours but also simultaneously identify the locations where the behaviours occur. Combined with other data streams, this method will allow researchers to further investigate the influence of different environmental characteristics on these behaviours, potentially leading the development of more effective, longer lasting interventions to promote movement and reduce stationary behaviour, ultimately improving the health of office workers.