scholarly journals Using Accelerometer Data to Tune the Parameters of an Extended Kalman Filter for Optical Motion Capture: Preliminary Application to Gait Analysis

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 427
Author(s):  
Javier Cuadrado ◽  
Florian Michaud ◽  
Urbano Lugrís ◽  
Manuel Pérez Soto
Keyword(s):  
Kalman Filter ◽  
Gait Analysis ◽  
Extended Kalman Filter ◽  
Motion Capture ◽  
Reference Frames ◽  
Preliminary Test ◽  
Accelerometer Data ◽  
Capture Process ◽  
Optical Motion ◽  
Optical Motion Capture

Optical motion capture is currently the most popular method for acquiring motion data in biomechanical applications. However, it presents a number of problems that make the process difficult and inefficient, such as marker occlusions and unwanted reflections. In addition, the obtained trajectories must be numerically differentiated twice in time in order to get the accelerations. Since the trajectories are normally noisy, they need to be filtered first, and the selection of the optimal amount of filtering is not trivial. In this work, an extended Kalman filter (EKF) that manages marker occlusions and undesired reflections in a robust way is presented. A preliminary test with inertial measurement units (IMUs) is carried out to determine their local reference frames. Then, the gait analysis of a healthy subject is performed using optical markers and IMUs simultaneously. The filtering parameters used in the optical motion capture process are tuned in order to achieve good correlation between the obtained accelerations and those measured by the IMUs. The results show that the EKF provides a robust and efficient method for optical system-based motion analysis, and that the availability of accelerations measured by inertial sensors can be very helpful for the adjustment of the filters.

A gait analysis using optical motion capture system with large scale pressure sensor

2017 ◽  
Vol 2017 (0) ◽  
pp. A-36
Author(s):  
Tatsuro Ishizuka ◽  
Tokio Maeda ◽  
Sakura Yamaji ◽  
Yuji Ohgi ◽  
Humiaki Shibayama ◽  
...  
Keyword(s):  
Gait Analysis ◽  
Motion Capture ◽  
Pressure Sensor ◽  
Large Scale ◽  
Motion Capture System ◽  
Optical Motion ◽  
Optical Motion Capture

Method for Testing Motion Analysis Laboratory Measurement Systems

2010 ◽  
Vol 132 (11) ◽  
Author(s):  
Marko J. Hakkarainen ◽  
Timo Bragge ◽  
Tuomas Liikavainio ◽  
Jari Arokoski ◽  
Pasi A. Karjalainen ◽  
...  
Keyword(s):  
Motion Analysis ◽  
Motion Capture ◽  
Accelerometer Data ◽  
Motion Capture System ◽  
Measurement Systems ◽  
Optical Motion ◽  
Analysis Laboratory ◽  
Vector Orientation ◽  
Equation Group ◽  
Optical Motion Capture

This paper proposes a method for comparing data from accelerometers, optical based 3D motion capture systems, and force platforms (FPs) in the context of spatial and temporal differences. Testing method is based on the motion laboratory accreditation test (MLAT), which can be used to test FP and camera based motion capture components of a motion analysis laboratory. This study extends MLAT to include accelerometer data. Accelerometers were attached to a device similar to the MLAT rod. The elevation of the rod from the plane of the floor is computed and compared with the force platform vector orientation and the rod orientation obtained by optical motion capture system. Orientation of the test device is achieved by forming nonlinear equation group, which describes the components of the measured accelerations. Solution for this equation group is estimated by using the Gauss–Newton method. This expanded MLAT procedure can be used in the laboratory setting were either FP, camera based motion capture, or any other motion capture system is used along with accelerometer measurements.

scholarly journals Comparison of Gait Analysis Between a Triaxial Accelerometer-Based Device and an Optical Motion Capture System

2020 ◽  
Author(s):  
Taisuke Ito ◽  
Yuichi Ota
Keyword(s):  
Gait Analysis ◽  
Motion Capture ◽  
Measurement Accuracy ◽  
Reaction Force ◽  
Correlation Coefficients ◽  
P Value ◽  
Motion Capture System ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Good Agreement

AYUMI EYE is an accelerometer-based gait analysis device that measures the 3D accelerations of the human trunk. This study investigated the measurement accuracy of the AYUMI EYE as hardware as well as the accuracy of the gait cycle extraction program via simultaneous measurements using AYUMI EYE, a ground reaction force (GRF), and an optical motion capture system called VICON. The study was conducted with four healthy individuals as participants. The gait data were obtained by simulating four different patterns for three trials each: normal walking, anterior-tilt walking, hemiplegic walking, and shuffling walking. The AYUMI EYE and VICON showed good agreement for both the acceleration and displacement data. The durations of subsequent stride cycles calculated using the AYUMI EYE and GRF were in good agreement based on the calculated cross-correlation coefficients (CCs) with an r value of 0.896 and p-value less than 0.05, and their accuracies for these results were sufficient.

Tracking of Markers for 2D and 3D Gait Analysis Using Home Video Cameras

2013 ◽  
Vol 4 (3) ◽  
pp. 36-52 ◽  
Author(s):  
Sandro Mihradi ◽  
Ferryanto ◽  
Tatacipta Dirgantara ◽  
Andi I. Mahyuddin
Keyword(s):  
Gait Analysis ◽  
Motion Capture ◽  
Motion Capture System ◽  
Distance Method ◽  
Home Video ◽  
Video Cameras ◽  
Optical Motion ◽  
Spatio Temporal ◽  
Optical Motion Capture ◽  
2D And 3D

This work presents the development of an affordable optical motion-capture system which uses home video cameras for 2D and 3D gait analysis. The 2D gait analyzer system consists of one camcorder and one PC while the 3D gait analyzer system uses two camcorders, a flash and two PCs. Both systems make use of 25 fps camcorder, LED markers and technical computing software to track motions of markers attached to human body during walking. In the experiment for 3D gait analyzer system, the two cameras are synchronized by using flash. The recorded videos for both systems are extracted into frames and then converted into binary images, and bridge morphological operation is applied for unconnected pixel to facilitate marker detection process. Least distance method is then employed to track the markers motions, and 3D Direct Linear Transformation is used to reconstruct 3D markers positions. The correlation between length in pixel and in the real world resulted from calibration process is used to reconstruct 2D markers positions. To evaluate the reliability of the 2D and 3D optical motion-capture system developed in the present work, spatio-temporal and kinematics parameters calculated from the obtained markers positions are qualitatively compared with the ones from literature, and the results show good compatibility.

scholarly journals Gap Reconstruction in Optical Motion Capture Sequences Using Neural Networks

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6115
Author(s):  
Przemysław Skurowski ◽  
Magdalena Pawlyta
Keyword(s):  
Neural Networks ◽  
Motion Capture ◽  
Matrix Completion ◽  
Input Sequence ◽  
Feedforward Neural Networks ◽  
Network Architectures ◽  
Motion Data ◽  
Optical Motion ◽  
Body Kinematic ◽  
Optical Motion Capture

Optical motion capture is a mature contemporary technique for the acquisition of motion data; alas, it is non-error-free. Due to technical limitations and occlusions of markers, gaps might occur in such recordings. The article reviews various neural network architectures applied to the gap-filling problem in motion capture sequences within the FBM framework providing a representation of body kinematic structure. The results are compared with interpolation and matrix completion methods. We found out that, for longer sequences, simple linear feedforward neural networks can outperform the other, sophisticated architectures, but these outcomes might be affected by the small amount of data availabe for training. We were also able to identify that the acceleration and monotonicity of input sequence are the parameters that have a notable impact on the obtained results.

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