@inproceedings{2040ab31b6244a31a98843147d15e60d,
title = "Filtering with rhythms: Application to estimation of gait cycle",
abstract = "The aim of this paper is to describe a coupled oscillator model for Bayesian inference. The coupled oscillator model comprises of a large number of oscillators with mean-field coupling. The collective dynamics of the oscillators are used to solve an inference problem: the empirical distribution of the population encodes a belief state' (posterior distribution) that is continuously updated based on noisy measurements. In effect, the coupled oscillator model works as a particle filter. The framework is described here with the aid of a model problem involving estimation of a walking gait cycle. For this problem, the coupled oscillator particle filter is developed, and demonstrated on experimental data taken from an Ankle-foot Orthosis (AFO) device.",
author = "Tilton, {Adam K.} and Hsiao-Wecksler, {Elizabeth T.} and Mehta, {Prashant G.}",
year = "2012",
doi = "10.1109/acc.2012.6315665",
language = "English (US)",
isbn = "9781457710957",
series = "Proceedings of the American Control Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3433--3438",
booktitle = "2012 American Control Conference, ACC 2012",
address = "United States",
note = "2012 American Control Conference, ACC 2012 ; Conference date: 27-06-2012 Through 29-06-2012",
}