Name
Abstract | ||
|---|---|---|
Human back movement estimation is clinically important for assessing patients with back pain. Most current techniques are limited to simple spinal movement angles without consideration of surrounding muscle movement and backplane rotation and torsion. These three dimensional analysis is fraught with difficulties due to the complex nature of the movement and sensor placement. In this paper, a consistent method based on multiple Body Sensor Network (BSN) nodes for the measurement of 3D bending and twist of the back is proposed. In our method, five BSN nodes, each consisting of a three axis accelerometer, a gyroscope and a magnetometer, are placed at the human back. Euler angles are then defined to represent the orientation for human back segments, kinematics analysis is then derived. An unscented Kalman filter (UKF) is deployed to estimate the defined Euler angles. Detailed experimental results have shown the feasibility and effectiveness of the proposed measurement and analysis framework. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/BSN.2011.15 | BSN |
Keywords | Field | DocType |
proposed measurement,consistent method,bsn node,kinematics analysis,movement analysis,analysis framework,simple spinal movement angle,movement estimation,muscle movement,euler angle,dimensional analysis,kinematics,euler angles,accelerometers,orientation,magnetometers,kalman filters,kalman filter,neurophysiology,unscented kalman filter,estimation | Computer vision,Gyroscope,Kinematics,Torsion (mechanics),Control theory,Computer science,Accelerometer,Euler angles,Kalman filter,Human back,Artificial intelligence,Wireless sensor network | Conference |
ISSN | ISBN | Citations |
2376-8886 | 978-1-4577-0469-7 | 4 |
PageRank | References | Authors |
0.47 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhiqiang Zhang | 1 | 198 | 24.54 |
| Julien Pansiot | 2 | 67 | 7.92 |
| Benny Lo | 3 | 403 | 37.89 |
| Guang-Zhong Yang | 4 | 2812 | 297.66 |