@article{ref1,
title="Adaptive change-point detection for studying human locomotion",
journal="Annual International Conference of the IEEE Engineering in Medicine and Biology Society.",
year="2021",
author="Jung, Sylvain and Oudre, Laurent and Truong, Charles and Dorveaux, Eric and Gorintin, Louis and Vayatis, Nicolas and Ricard, Damien",
volume="2021",
number="",
pages="2020-2024",
abstract="This paper presents an innovative method to analyze inertial signals recorded in a semi-controlled environment. It uses an adaptive and supervised change point detection procedure to decompose the signals into homogeneous segments, allowing a refined analysis of the successive phases within a gait protocol. Thanks to a training procedure, the algorithm can be applied to a wide range of protocols and handles different levels of granularity. The method is tested on a cohort of 15 healthy subjects performing a complex protocol composed of different activities and shows promising results for the automated and adaptive study of human gait and activity.  Clinical relevance- A new approach to study human activity and locomotion in Free-Living Environments FLEs through an adaptive change-point detection which isolates homogeneous phases.<p /> <p>Language: en</p>",
language="en",
issn="2375-7477",
doi="10.1109/EMBC46164.2021.9629775",
url="http://dx.doi.org/10.1109/EMBC46164.2021.9629775"
}