Universität zu Köln

Ghosh, Sayantan ORCID: 0000-0001-7200-6856, Fleiner, Tim, Giannouli, Eleftheria ORCID: 0000-0001-7762-1348, Jaekel, Uwe ORCID: 0000-0002-4275-1430, Mellone, Sabato ORCID: 0000-0001-7688-0188, Haeussermann, Peter and Zijlstra, Wiebren (2018). Statistical learning of mobility patterns from long-term monitoring of locomotor behaviour with body-worn sensors. Sci Rep, 8. LONDON: NATURE PUBLISHING GROUP. ISSN 2045-2322

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Abstract

Long term monitoring of locomotor behaviour in humans using body-worn sensors can provide insight into the dynamical structure of locomotion, which can be used for quantitative, predictive and classification analyses in a biomedical context. A frequently used approach to study daily life locomotor behaviour in different population groups involves categorisation of locomotion into various states as a basis for subsequent analyses of differences in locomotor behaviour. In this work, we use such a categorisation to develop two feature sets, namely state probability and transition rates between states, and use supervised classification techniques to demonstrate differences in locomotor behaviour. We use this to study the influence of various states in differentiating between older adults with and without dementia. We further assess the contribution of each state and transition and identify the states most influential in maximising the classification accuracy between the two groups. The methods developed here are general and can be applied to areas dealing with categorical time series.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Ghosh, Sayantan UNSPECIFIED orcid.org/0000-0001-7200-6856 UNSPECIFIED Fleiner, Tim UNSPECIFIED UNSPECIFIED UNSPECIFIED Giannouli, Eleftheria UNSPECIFIED orcid.org/0000-0001-7762-1348 UNSPECIFIED Jaekel, Uwe UNSPECIFIED orcid.org/0000-0002-4275-1430 UNSPECIFIED Mellone, Sabato UNSPECIFIED orcid.org/0000-0001-7688-0188 UNSPECIFIED Haeussermann, Peter UNSPECIFIED UNSPECIFIED UNSPECIFIED Zijlstra, Wiebren UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-186644
DOI:	10.1038/s41598-018-25523-4
Journal or Publication Title:	Sci Rep
Volume:	8
Date:	2018
Publisher:	NATURE PUBLISHING GROUP
Place of Publication:	LONDON
ISSN:	2045-2322
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language PHYSICAL-ACTIVITY Multiple languages Multidisciplinary Sciences Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/18664