Davoudi Anis, Shickel Benjamin, Tighe Patrick James, Bihorac Azra, Rashidi Parisa
Department of Biomedical Engineering, University of Florida, Gainesville, FL, United States.
Department of Medicine, University of Florida, Gainesville, FL, United States.
Front Digit Health. 2022 May 17;4:773387. doi: 10.3389/fdgth.2022.773387. eCollection 2022.
Patients in critical care settings often require continuous and multifaceted monitoring. However, current clinical monitoring practices fail to capture important functional and behavioral indices such as mobility or agitation. Recent advances in non-invasive sensing technology, high throughput computing, and deep learning techniques are expected to transform the existing patient monitoring paradigm by enabling and streamlining granular and continuous monitoring of these crucial critical care measures. In this review, we highlight current approaches to pervasive sensing in critical care and identify limitations, future challenges, and opportunities in this emerging field.
重症监护环境中的患者通常需要持续且多方面的监测。然而,当前的临床监测方法未能捕捉到诸如活动能力或躁动等重要的功能和行为指标。无创传感技术、高通量计算和深度学习技术的最新进展有望通过实现并简化对这些关键重症监护措施的精细且持续监测,来改变现有的患者监测模式。在本综述中,我们重点介绍了重症监护中普遍传感的当前方法,并确定了这一新兴领域的局限性、未来挑战和机遇。