Estimating physical ability of stroke patients without specific tests

Publication Type Conference Paper
Authors Adrian Derungs, Julia Seiter, Corina Schuster-Amft, Oliver Amft
Title Estimating physical ability of stroke patients without specific tests
Abstract We estimate the Extended Barthel Index (EBI) in patients after stroke using inertial sensor measurements acquired during daily activity, rather than specific assessments. The EBI is a standard clinical assessment showing patient independence in handling everyday tasks. Our work aims at providing a continuous ability estimate for patients and therapists that could be used without expert supervision. We extract nine activity primitives (AP), including sitting, standing, transition, etc. from the continuous sensor data using basic rules that do not require data-based training. Using the relative duration of activity primitives, we evaluate the EBI score estimation using two regression methods: Generalised Linear Models (GLM) and Support-Vector Regression (SVR). We evaluated our approaches in full-day study recordings from 11 stroke patients with totally 102 days in ambulatory rehabilitation in a day-care centre. Our results show that EBI can be estimated from the activity primitives with approximately 12% relative error on average for all study participants using SVR. Our results indicate that EBI can be estimated in daily life activity, thus supporting patients and therapists in tracking rehab progress.
Date 2015
Proceedings Title Proceedings of the 2015 ACM International Symposium on Wearable Computers (ISWC '15)
Publisher ACM Press
Pages 137-140
Language en
DOI 10.1145/2802083.2808412
ISBN 978-1-4503-3578-2
URL Publisher's website
Library Catalog Crossref
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Friedrich-Alexander-Universität Erlangen-Nürnberg