Department of Information Science and Engineering, Saga University, Saga 8408502, Japan.
Faculty of Science and Engineering, Saga University, Saga 8408502, Japan.
Sensors (Basel). 2023 May 30;23(11):5212. doi: 10.3390/s23115212.
Fall Detection Systems (FDS) are automated systems designed to detect falls experienced by older adults or individuals. Early or real-time detection of falls may reduce the risk of major problems. This literature review explores the current state of research on FDS and its applications. The review shows various types and strategies of fall detection methods. Each type of fall detection is discussed with its pros and cons. Datasets of fall detection systems are also discussed. Security and privacy issues related to fall detection systems are also considered in the discussion. The review also examines the challenges of fall detection methods. Sensors, algorithms, and validation methods related to fall detection are also talked over. This work found that fall detection research has gradually increased and become popular in the last four decades. The effectiveness and popularity of all strategies are also discussed. The literature review underscores the promising potential of FDS and highlights areas for further research and development.
跌倒检测系统（FDS）是为检测老年人或个体经历的跌倒而设计的自动化系统。及早或实时检测跌倒可能会降低出现重大问题的风险。本文献综述探讨了 FDS 及其应用的当前研究状况。综述展示了各种类型和策略的跌倒检测方法。每种类型的跌倒检测都讨论了其优缺点。还讨论了跌倒检测系统的数据集。在讨论中还考虑了与跌倒检测系统相关的安全和隐私问题。该综述还研究了跌倒检测方法面临的挑战。还讨论了与跌倒检测相关的传感器、算法和验证方法。这项研究发现，在过去的四十年中，跌倒检测研究逐渐增加并变得流行。还讨论了所有策略的有效性和普及性。文献综述强调了 FDS 的有前途的潜力，并突出了进一步研究和开发的领域。
