School of Public Health, Prevention Research Collaboration, Charles Perkins Centre, The University of Sydney, Sydney, Australia.
Sydney Informatics Hub, The University of Sydney, Sydney, Australia.
Ergonomics. 2022 May;65(5):675-690. doi: 10.1080/00140139.2021.1980115. Epub 2021 Sep 27.
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 ( = 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. 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.
长时间保持静止的行为是许多办公场所常见的现象，这种行为与一系列身体疾病有关。研究这种行为的身体环境可能是开发有效干预措施的关键。本研究旨在通过在办公环境中收集的 5 天时空数据的分割，来估计和定位办公室工作人员（n=10）的静止和运动行为。与参考数据相比，该分割方法在观察分类方面的准确率达到了≥85.5%，在回合分类方面的准确率达到了≥90%。研究结果表明，工作人员大部分时间处于静止状态（Mean=86.4%），平均每小时有 28.4 个静止回合和 25.9 个运动回合。虽然这些发现与其他研究一致，但分割后的数据也进行了可视化处理，结果显示工作人员在多个位置处于静止状态≥5 分钟，并且这些位置随着时间的推移而变化。本研究应用数据分割方法对在办公场所收集的时空数据进行分类，以确定静止和运动行为。分割后的数据不仅揭示了发生的行为，还揭示了其位置、持续时间和时间。分割时空数据可以为工作场所研究提供有价值的物理背景。
