TY  - JOUR
PY  - 2013//
TI  - Rider trunk and bicycle pose estimation with fusion of force/inertial sensors
JO  - IEEE transactions on bio-medical engineering
A1  - Zhang, Yizhai
A1  - Chen, Kuo
A1  - Yi, Jingang
SP  - 2541
EP  - 2551
VL  - 60
IS  - 9
N2  - Estimation of human pose in physical humanmachine interactions such as bicycling is challenging because of highly-dimensional human motion and lack of inexpensive, effective motion sensors. In this paper, we present a computational scheme to estimate both the rider trunk pose and the bicycle roll angle using only inertial and force sensors. The estimation scheme is built on a rider-bicycle dynamic model and the fusion of the wearable inertial sensors and the bicycle force sensors. We take advantages of the attractive properties of the robust force measurements and the motion-sensitive inertial measurements. The rider-bicycle dynamic model provides the underlying relationship between the force and the inertial measurements. The extended Kalman filter-based sensor fusion design fully incorporates the dynamic effects of the force measurements. The performance of the estimation scheme are demonstrated through extensive indoor and outdoor riding experiments.<p />  <p>Language: en</p>
LA  - en
SN  - 0018-9294
UR  - http://dx.doi.org/10.1109/TBME.2013.2260339
ID  - ref1
ER  -