Zhao Guangyang, Chen Liming, Ning Huansheng
School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100089, China.
School of Computing, University of Ulster, Newtownabbey BT37 0QB, UK.
Healthcare (Basel). 2021 Oct 27;9(11):1448. doi: 10.3390/healthcare9111448.
Fall is a major problem leading to serious injuries in geriatric populations. Sensor-based fall risk assessment is one of the emerging technologies to identify people with high fall risk by sensors, so as to implement fall prevention measures. Research on this domain has recently made great progress, attracting the growing attention of researchers from medicine and engineering. However, there is a lack of studies on this topic which elaborate the state of the art. This paper presents a comprehensive survey to discuss the development and current status of various aspects of sensor-based fall risk assessment. Firstly, we present the principles of fall risk assessment. Secondly, we show knowledge of fall risk monitoring techniques, including wearable sensor based and non-wearable sensor based. After that we discuss features which are extracted from sensors in fall risk assessment. Then we review the major methods of fall risk modeling and assessment. We also discuss some challenges and promising directions in this field at last.
跌倒在老年人群中是一个导致严重伤害的主要问题。基于传感器的跌倒风险评估是一种新兴技术，通过传感器识别跌倒风险高的人群，以便实施预防跌倒措施。该领域的研究最近取得了很大进展，吸引了医学和工程领域研究人员越来越多的关注。然而，缺乏阐述该领域技术现状的研究。本文进行了全面综述，以讨论基于传感器的跌倒风险评估各方面的发展和现状。首先，我们介绍跌倒风险评估的原理。其次，我们展示跌倒风险监测技术的相关知识，包括基于可穿戴传感器和基于非可穿戴传感器的技术。之后，我们讨论在跌倒风险评估中从传感器提取的特征。然后，我们回顾跌倒风险建模和评估的主要方法。最后，我们还讨论了该领域的一些挑战和有前景的方向。
