Position Tracking During Human Walking Using an Integrated Wearable Sensing System
| Autor: | Zizzo, Giulio, Ren, Lei |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
ResearchInstitutes_Networks_Beacons/MICRA
wearable sensors ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Walking pedestrian dead reckoning lcsh:Chemical technology Article Motion Wearable Electronic Devices Manchester Institute for Collaborative Research on Ageing Humans lcsh:TP1-1185 Kalman filter IMU navigation Algorithms |
| Zdroj: | Zizzo, G & Ren, L 2017, ' Position Tracking During Human Walking Using an Integrated Wearable Sensing System ', Sensors, vol. 17, no. 12, 2866 . https://doi.org/10.3390/s17122866 Sensors, Vol 17, Iss 12, p 2866 (2017) Sensors (Basel, Switzerland) |
| DOI: | 10.3390/s17122866 |
| Popis: | Progress has been made enabling expensive, high-end inertial measurement units (IMUs) to be used as tracking sensors. However, the cost of these IMUs is prohibitive to their widespread use, and hence the potential of low-cost IMUs is investigated in this study. A wearable low-cost sensing system consisting of IMUs and ultrasound sensors was developed. Core to this system is an extended Kalman filter (EKF), which provides both zero-velocity updates (ZUPTs) and Heuristic Drift Reduction (HDR). The IMU data was combined with ultrasound range measurements to improve accuracy. When a map of the environment was available, a particle filter was used to impose constraints on the possible user motions. The system was therefore composed of three subsystems: IMUs, ultrasound sensors, and a particle filter. A Vicon motion capture system was used to provide ground truth information, enabling validation of the sensing system. Using only the IMU, the system showed loop misclosure errors of 1% with a maximum error of 4-5% during walking. The addition of the ultrasound sensors resulted in a 15% reduction in the total accumulated error. Lastly, the particle filter was capable of providing noticeable corrections, which could keep the tracking error below 2% after the first few steps. |
| Databáze: | OpenAIRE |
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