Abstract: The fall detection system based on the wearable device can detect the fall behavior of the person and is widely used in the scene of the elderly monitoring, and the design of the related system has also attracted the attention of many researchers. This paper gives a detailed review of the research on the fall detection system based on wearable devices. It introduces the process of falling. According to the workflow of the wearable device fall detection system, it introduces the current research work from data acquisition, data preprocessing, feature extraction and discriminant algorithms. Aiming to provide meaningful reference and reference for subsequent research work, it also classifies, compares and statistically analyzes existing research results.

Key words: wearable device, fall detection, data acquisition, feature extraction, machine learning

摘要： 基于可穿戴设备的跌倒检测系统能检测人的跌倒行为，并在老人监护等场景下得到广泛应用，相关系统的设计也引起众多研究人员的关注。对于基于可穿戴设备的跌倒检测系统的研究情况做了详细综述，介绍了跌倒的过程，按照可穿戴设备跌倒检测系统的工作流程，分别从数据采集、数据预处理、特征提取和判别算法等几个方面介绍目前研究工作的开展情况，并对已有研究成果进行分类、对比和统计分析，为后续研究工作提供有意义的借鉴与参考。

关键词: 可穿戴设备, 跌到检测, 数据采集, 特征提取, 机器学习