Inertial Sensor-Based Smoother for Gait Analysis

Sensors

关键词: gait analysis;    smoother;    inertial sensors;    inertial navigation algorithm;   

DOI  :  10.3390/s141224338

来源: mdpi

【 摘 要 】

An off-line smoother algorithm is proposed to estimate foot motion using an inertial sensor unit (three-axis gyroscopes and accelerometers) attached to a shoe. The smoother gives more accurate foot motion estimation than filter-based algorithms by using all of the sensor data instead of using the current sensor data. The algorithm consists of two parts. In the first part, a Kalman filter is used to obtain initial foot motion estimation. In the second part, the error in the initial estimation is compensated using a smoother, where the problem is formulated in the quadratic optimization problem. An efficient solution of the quadratic optimization problem is given using the sparse structure. Through experiments, it is shown that the proposed algorithm can estimate foot motion more accurately than a filter-based algorithm with reasonable computation time. In particular, there is significant improvement in the foot motion estimation when the foot is moving off the floor: the z-axis position error squared sum (total time: 3.47 s) when the foot is in the air is 0.0807 m² (Kalman filter) and 0.0020 m² (the proposed smoother).

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.