Design of Gait Detection System Based on FCM Algorithm

Xiaochen Guo, Chao Yang, Xuanlin Chen, Tongle Xu
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Abstract

Gait detection technology is widely used in medical and military fields. The key of gait detection technology is low cost, high accuracy and portable detection equipment and real-time detection algorithm. This paper introduces a real-time gait detection system, this kind of gait detection system using machine learning algorithm based on FCM clustering analysis and calibration of the sensor data filter algorithm based on rules, the kinematic data is divided into five different gait events, namely the heel strike , foot flat, heel off , toe off and initial swing phase . Compared with 3D posture capture experiment equipment, the accuracy of gait event detection of the proposed gait detection system is verified to be highly reliable.
基于FCM算法的步态检测系统设计
步态检测技术在医学和军事领域有着广泛的应用。步态检测技术的关键是低成本、高精度、便携式检测设备和实时检测算法。本文介绍了一种实时步态检测系统,这种步态检测系统采用基于机器学习算法的FCM聚类分析和基于规则的传感器数据滤波算法标定,将运动学数据划分为5个不同的步态事件,即脚跟撞击、足部平、脚跟脱落、脚趾脱落和初始摆动阶段。通过与三维姿态捕捉实验设备的对比,验证了所提出的步态检测系统对步态事件检测的准确性具有较高的可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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