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.
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