@inproceedings{7ee2a929376241a9adac5e373146bea2,
title = "ANN-based stride detection using smartphones for Pedestrian dead reckoning",
abstract = "Position awareness is a very important issue for internet of thing (IoT) applications using smartphones. Pedestrian dead reckoning (PDR) is one of the methods used to estimate a user's indoor position. The accuracy of a stride detection is very important to guarantee the estimation accuracy of the user location. This paper proposes an algorithm to detect the stride using acceleration spectrogram feature by utilizing the accelerometer in a smartphone. An artificial neural network (ANN) technology is applied to detect the stride. The proposed algorithm has an accuracy of 97.7% for stride detection.",
author = "Youngwoo Kim and Eyobu, {Odongo Steven} and Han, {Dong Seog}",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Conference on Consumer Electronics, ICCE 2018 ; Conference date: 12-01-2018 Through 14-01-2018",
year = "2018",
month = mar,
day = "26",
doi = "10.1109/ICCE.2018.8326239",
language = "English",
series = "2018 IEEE International Conference on Consumer Electronics, ICCE 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1--2",
editor = "Mohanty, {Saraju P.} and Peter Corcoran and Hai Li and Anirban Sengupta and Jong-Hyouk Lee",
booktitle = "2018 IEEE International Conference on Consumer Electronics, ICCE 2018",
address = "United States",
}