An Adaptive-Gain Complementary Filter for Real-Time Human Motion Tracking With MARG Sensors in Free-Living Environments

2013 ◽  
Vol 21 (2) ◽  
pp. 254-264 ◽  
Author(s):  
Ya Tian ◽  
Hongxing Wei ◽  
Jindong Tan
Keyword(s):  
Real Time ◽  
Motion Tracking ◽  
Human Motion ◽  
Free Living ◽  
Human Motion Tracking ◽  
Complementary Filter ◽  
Living Environments

scholarly journals Estimating Three-Dimensional Body Orientation Based on an Improved Complementary Filter for Human Motion Tracking

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3765 ◽  
Author(s):  
Chunzhi Yi ◽  
Jiantao Ma ◽  
Hao Guo ◽  
Jiahong Han ◽  
Hefu Gao ◽  
...  
Keyword(s):  
Motion Tracking ◽  
Filter Design ◽  
Angular Rate ◽  
Human Motion ◽  
Body Orientation ◽  
Measurement Unit ◽  
Test Machine ◽  
Gradient Descent Method ◽  
Human Motion Tracking ◽  
Complementary Filter

Rigid body orientation determined by IMU (Inertial Measurement Unit) is widely applied in robotics, navigation, rehabilitation, and human-computer interaction. In this paper, aiming at dynamically fusing quaternions computed from angular rate integration and FQA algorithm, a quaternion-based complementary filter algorithm is proposed to support a computationally efficient, wearable motion-tracking system. Firstly, a gradient descent method is used to determine a function from several sample points. Secondly, this function is used to dynamically estimate the fusion coefficient based on the deviation between measured magnetic field, gravity vectors and their references in Earth-fixed frame. Thirdly, a test machine is designed to evaluate the performance of designed filter. Experimental results validate the filter design and show its potential of real-time human motion tracking.

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