Abstract

The work of nurses is often associated with elevated anxiety, negative affect, and fatigue, all of which may impact both the quality of patient care and their own well-being. It is critical to understand behavioral patterns, such as human movement, that may be associated with these workplace challenges of nurses. These movement behaviors include location-based movement patterns and dynamical changes of movement intensity. Particularly, we investigated these movement-related patterns for 75 nurses, using wearable sensor recordings, collected over a continuous period of ten weeks. We first discover the location of movement patterns from the Bluetooth proximity data using topic models. We then extract the heart rate zone features from PPG readings to infer the intensity of physical movement. Our results show that the location movement patterns and dynamical changes of movement intensity offer key insights …

Date

2020

Authors

Tiantian Feng, Shrikanth Narayanan

Conference

2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

Pages

4256-4260

Publisher

IEEE