Feng Tiantian, Narayanan Shrikanth
Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:4256-4260. doi: 10.1109/EMBC44109.2020.9176318.
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 into understanding the workplace behavior of the nursing population in a complex hospital setting.
护士的工作常常与焦虑加剧、负面情绪和疲劳相关,所有这些都可能影响患者护理质量以及护士自身的幸福感。了解可能与护士面临的这些工作场所挑战相关的行为模式,如人体运动,至关重要。这些运动行为包括基于位置的运动模式和运动强度的动态变化。特别是,我们使用连续十周收集的可穿戴传感器记录,对75名护士的这些与运动相关的模式进行了调查。我们首先使用主题模型从蓝牙接近度数据中发现运动模式的位置。然后,我们从PPG读数中提取心率区特征,以推断身体运动的强度。我们的结果表明,位置运动模式和运动强度的动态变化为理解复杂医院环境中护理人群的工作场所行为提供了关键见解。