Citation

Elyasi F, Manduchi R. IEEE eXplor 2023; 2023.

Copyright

(Copyright © 2023, IEEE Service Center)

DOI

10.1109/ipin57070.2023.10332483

PMID

38152683

PMCID

PMC10752414

Abstract

Pedestrian dead reckoning (PDR) relies on the estimation of the length of each step taken by the walker in a path from inertial data (e.g. as recorded by a smartphone). Existing algorithms either estimate step lengths directly, or predict walking speed, which can then be integrated over a step period to obtain step length. We present an analysis, using a common architecture formed by an LSTM followed by four fully connected layers, of the quality of reconstruction when predicting step length vs. walking speed. Our experiments, conducted on a data set collected by twelve participants, strongly suggest that step length can be predicted more reliably than average walking speed over each step.

Language: en

Keywords

Pedestrian dead reckoning (PDR); Smartphone inertial data; Step length estimation; Walking speed prediction