loading
Papers

Research.Publish.Connect.

Paper

Paper Unlock

Authors: L. Palmerini 1 ; L. Rocchi 1 ; S. Mellone 1 ; L. Chiari 1 and F. Valzania 2

Affiliations: 1 University of Bologna, Italy ; 2 University of Modena and Reggio Emilia, Italy

ISBN: 978-989-8425-28-7

Keyword(s): Feature Selection, Parkinson’s Disease, Accelerometer.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; BioInformatics & Pattern Discovery ; Data Reduction and Quality Assessment ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Mining High-Dimensional Data ; Symbolic Systems

Abstract: The Timed Up and Go (TUG) is a widely used clinical test to assess mobility and fall risk in Parkinson’s disease (PD). The traditional outcome of this test is its duration. Since this single measure cannot provide insight on subtle differences in test performances, we considered an instrumented TUG (iTUG). The aim was to find, by means of a feature selection, the best set of quantitative measures that would allow an objective evaluation of gait function in PD. We instrumented the TUG using a triaxial accelerometer. Twenty early-mild PD and twenty age-matched control subjects performed normal and dual task TUG trials. Several temporal, coordination and smoothness measures were extracted from the acceleration signals; a wrapper feature selection was implemented for different classifiers with an exhaustive search for subsets from 1 to 3 features. A leave-one-out cross validation (LOOCV) was implemented both for the feature selection and for the evaluation of the classifier, resulting in a nested LOOCV. The resulting selected features permit to obtain a good accuracy (7.5% of misclassification rate) in the classification of PD. Interestingly the traditional TUG duration was not selected in any of the best subsets. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.85.245.126

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Palmerini, L.; Rocchi, L.; Mellone, S.; Chiari, L. and Valzania, F. (2010). FEATURE SELECTION FOR THE INSTRUMENTED TIMED UP AND GO IN PARKINSON’S DISEASE.In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2010) ISBN 978-989-8425-28-7, pages 95-99. DOI: 10.5220/0003100400950099

@conference{kdir10,
author={L. Palmerini. and L. Rocchi. and S. Mellone. and L. Chiari. and F. Valzania.},
title={FEATURE SELECTION FOR THE INSTRUMENTED TIMED UP AND GO IN PARKINSON’S DISEASE},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2010)},
year={2010},
pages={95-99},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003100400950099},
isbn={978-989-8425-28-7},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2010)
TI - FEATURE SELECTION FOR THE INSTRUMENTED TIMED UP AND GO IN PARKINSON’S DISEASE
SN - 978-989-8425-28-7
AU - Palmerini, L.
AU - Rocchi, L.
AU - Mellone, S.
AU - Chiari, L.
AU - Valzania, F.
PY - 2010
SP - 95
EP - 99
DO - 10.5220/0003100400950099

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.