| Literature DB >> 28242567 |
Paul Vasilyev1, Sean Pearson1, Mahmoud El-Gohary2, Mateo Aboy1, James McNames3.
Abstract
Wearable devices with embedded kinematic sensors including triaxial accelerometers, gyroscopes, and magnetometers are becoming widely used in applications for tracking human movement in domains that include sports, motion gaming, medicine, and wellness. The kinematic sensors can be used to estimate orientation, but can only estimate changes in position over short periods of time. We developed a prototype sensor that includes ultra wideband ranging sensors and kinematic sensors to determine the feasibility of fusing the two sensor technologies to estimate both orientation and position. We used a state space model and applied the unscented Kalman filter to fuse the sensor information. Our results demonstrate that it is possible to estimate orientation and position with less error than is possible with either sensor technology alone. In our experiment we obtained a position root mean square error of 5.2cm and orientation error of 4.8° over a 15min recording.Entities:
Keywords: Bayesian estimation; Indoor positioning; Ultra wideband (UWB)
Mesh:
Year: 2017 PMID: 28242567 PMCID: PMC5481529 DOI: 10.1016/j.gaitpost.2017.02.011
Source DB: PubMed Journal: Gait Posture ISSN: 0966-6362 Impact factor: 2.840