文献类型：会议论文

英文题名：Smart Floor System for Comprehensive Fall Detection: Enhancing Safety and Independence for the Elderly

作者：Li, Lin[1]; Jiang, Lei[2]; Han, Han[2]; Yuan, Keya[3]

第一作者：李琳

机构：[1] College of Applied Science and Technology, Beijing Union University, Beijing, China; [2] Research Institute of Health and Aging, China Electronics Engineering Design Institute Co. Ltd., Beijing, China; [3] College of Robotics, Beijing Union University, Beijing, China

第一机构：北京联合大学应用科技学院

通讯机构：[3]College of Robotics, Beijing Union University, Beijing, China|[1141739]北京联合大学机器人学院;[11417]北京联合大学;

会议论文集：Proceedings of 2024 5th International Symposium on Artificial Intelligence for Medicine Science, ISAIMS 2024

会议日期：August 13, 2024 - August 17, 2024

会议地点：Amsterdam, Netherlands

语种：英文

外文关键词：Wearable sensors

摘要：With the global aging population on the rise, fall-related injuries among the elderly pose significant health risks, making timely and accurate fall detection crucial. Traditional fall detection methods, including wearable sensors, ambient sensors, and camera-based systems, often face limitations such as user compliance, limited coverage, and privacy concerns. This paper proposes a novel human fall detection method utilizing a smart floor system that employs sensors combining capacitance and inductance. These sensors capture electrical properties data, which is then processed using data processing and analysis techniques to accurately detect and differentiate between various human postures such as standing, sitting, and lying down. This system addresses the shortcomings of existing technologies by providing comprehensive coverage without the need for user-worn devices and operates effectively irrespective of environmental conditions. By integrating this system into everyday environments, we can significantly enhance the safety and independence of the elderly, offering a reliable and cost-effective solution for fall detection. ? 2024 Copyright held by the owner/author(s).