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基于足底压力和关节运动信息的步态检测系统设计 被引量:2

Design of Gait Detection System Based on Joint Motion Information and Foot Pressure
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摘要 作为老年人高发疾病,脑卒中有着较高的几率造成患者行动障碍;及时检测、获取偏瘫患者行走时步态信息,是治疗师为患者制定康复计划的重要环节;目前,较新的步态检测系统大多采用三维分析,三维步态分析系统体积较大、成本高、操作不便,在患者主动康复训练中存在较大的局限;针对现今步态检测系统的局限,设计了一种结合无线传输技术,检测患者关节运动角度及足底压力的运动信息检测系统;系统采用薄膜压力传感器、惯性传感器分别采集足底压力及关节运动信息,实现了对患者的8路足底压力信息及下肢关节运动角度信息的快速、有效采集;实验表明,系统可以有效采集关节运动角度及足底压力信息,在未来的康复训练中有着很好的应用前景。 As a high incidence of senile diseases,stroke has a very high risk of causing mobility problems in patients.Timely detection,access to patients with walking hemiplegia gait information is the therapist for the patient to develop an important part of the rehabilitation plan.At present,the newer gait detection systems mostly use three-dimensional analysis,the three-dimensional gait analysis system is larger in size,high in cost and inconvenient in operation,and has great limitations in active rehabilitation training.In view of the limitation of current gait detection system,a motion information detection system combining wireless transmission technology and detecting the angle of joint movement and plantar pressure was designed.The system uses the membrane pressure sensor and the inertial sensor to collect the foot pressure and the joint movement information respectively,and realizes the quick and effective acquisition of the patient's 8-foot plantar pressure information and the lower limb joint movement angle information.Experiments show that the system can effectively collect the angle of joint motion and plantar pressure,and has good application prospect in future rehabilitation training.
作者 曾湛 李长俊 王春宝 Zeng Zhan;Li Changjun;Wang Chunbao(Guilin University of Electronic Technology,Guilin 541004,China;Institute of Information Technology,Guilin University of Electronic Technology,Guilin 541004,China;Shenzhen lnstitute of Geriatrics,Shenzhen 518000,China)
出处 《计算机测量与控制》 2018年第8期18-22,共5页 Computer Measurement &Control
基金 深圳市科技研发资金国际合作研究项目(GJHZ20170331105318685)
关键词 足底压力 惯性传感器 步态检测 foot pressure inertial sensor gait detection
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