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Open AccessArticle

Indoor Trajectory Reconstruction of Walking, Jogging, and Running Activities Based on a Foot-Mounted Inertial Pedestrian Dead-Reckoning System

1
Telematics Engineering Research Group, Telematics Department, Universidad Del Cauca (Unicauca), Popayán 190002, Colombia
2
Machine Learning and Data Analytics Lab, Computer Science Department, Friedrich-Alexander University Erlangen-Nürnberg (FAU), 91052 Erlangen, Germany
*
Authors to whom correspondence should be addressed.
Sensors 2020, 20(3), 651; https://doi.org/10.3390/s20030651
Received: 27 September 2019 / Revised: 22 October 2019 / Accepted: 1 November 2019 / Published: 24 January 2020
The evaluation of trajectory reconstruction of the human body obtained by foot-mounted Inertial Pedestrian Dead-Reckoning (IPDR) methods has usually been carried out in controlled environments, with very few participants and limited to walking. In this study, a pipeline for trajectory reconstruction using a foot-mounted IPDR system is proposed and evaluated in two large datasets containing activities that involve walking, jogging, and running, as well as movements such as side and backward strides, sitting, and standing. First, stride segmentation is addressed using a multi-subsequence Dynamic Time Warping method. Then, detection of Toe-Off and Mid-Stance is performed by using two new algorithms. Finally, stride length and orientation estimation are performed using a Zero Velocity Update algorithm empowered by a complementary Kalman filter. As a result, the Toe-Off detection algorithm reached an F-score between 90% and 100% for activities that do not involve stopping, and between 71% and 78% otherwise. Resulting return position errors were in the range of 0.5% to 8.8% for non-stopping activities and 8.8% to 27.4% otherwise. The proposed pipeline is able to reconstruct indoor trajectories of people performing activities that involve walking, jogging, running, side and backward walking, sitting, and standing. View Full-Text
Keywords: trajectory reconstruction; stride segmentation; dynamic time warping; pedestrian dead-reckoning trajectory reconstruction; stride segmentation; dynamic time warping; pedestrian dead-reckoning
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MDPI and ACS Style

Ceron, J.D.; Martindale, C.F.; López, D.M.; Kluge, F.; Eskofier, B.M. Indoor Trajectory Reconstruction of Walking, Jogging, and Running Activities Based on a Foot-Mounted Inertial Pedestrian Dead-Reckoning System. Sensors 2020, 20, 651.

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