基于压力中心稳定性理论的智能手杖机器人老年人跌倒检测

P. Di, Jian Huang, Shotaro Nakagawa, K. Sekiyama, T. Fukuda
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引用次数: 6

摘要

为帮助老年人和残疾人行走,设计了一种智能手杖机器人。该机器人由一根操纵杆、一组传感器和由三个瑞典轮驱动的全方位基础组成。使用多个传感器来识别用户的“行走意图”,该“行走意图”由一个称为意向方向(intentional direction, ITD)的新概念定量描述。基于滤波过渡段的导引,提出了一种基于意向的手杖机器人导纳运动控制方案。为了检测使用者的跌倒,提出了一种基于杜波依斯可能性理论的检测方法,该方法将力传感器、激光测距仪(LRF)和鞋上负载传感器的传感器信息结合起来进行检测。在二维空间中,利用压力中心(COP)与支撑三角形中心之间的相对位置作为人体跌倒模型的重要特征。通过实验验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fall detection for elderly by using an intelligent cane robot based on center of pressure (COP) stability theory
An intelligent cane robot was designed for aiding the elderly and handicapped people walking. The robot consists of a stick, a group of sensors and an omni-directional basis driven by three Swedish wheels. Multiple sensors were used to recognize the user's “walking intention”, which is quantitatively described by a new concept called intentional direction (ITD). Based on the guidance of filtered ITD, a novel intention-based admittance motion control (IBAC) scheme was proposed for the cane robot. To detect the fall of user, a detection method based on Dubois possibility theory was proposed using the combined sensor information from force sensors, a laser ranger finder (LRF) and an on-shoe load sensor. The human fall model was represented in a two-dimensional space, where the relative position between the center of pressure (COP) and the center of support triangle was utilized as a significant feature. The effectiveness of proposed fall detection method was also confirmed by experiments.
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