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Authors: Sandra Hellmers 1 ; Tobias Kromke 1 ; Lena Dasenbrock 1 ; Andrea Heinks 1 ; Jürgen M. Bauer 2 ; Andreas Hein 1 and Sebastian Fudickar 1

Affiliations: 1 Carl von Ossietzky University Oldenburg, Germany ; 2 Heidelberg University, Germany

ISBN: 978-989-758-281-3

Keyword(s): Stair Climb Power, Inertial Measurement Unit (IMU), Power, Stair Ascending, Machine Learning, Clinical Assessment, Unsupervised, Wearable Sensors.

Related Ontology Subjects/Areas/Topics: Biomedical Engineering ; Biomedical Signal Processing ; Devices ; Distributed and Mobile Software Systems ; Health Engineering and Technology Applications ; Health Information Systems ; Human-Computer Interaction ; Mobile Technologies ; Mobile Technologies for Healthcare Applications ; Neural Rehabilitation ; Neurotechnology, Electronics and Informatics ; Pattern Recognition and Machine Learning ; Physiological Computing Systems ; Software Engineering ; Wearable Sensors and Systems

Abstract: In order to initiate interventions at an early stage of functional decline and thus, to extend independent living, the early detection of changes in functional ability is important. The Stair Climb Power Test (SCPT) is a standard test in geriatric assessments for strength as one of the essential components of functional ability. This test is also well suited for regular and frequent power measurements in daily life since the activity of climbing stairs is usually frequently performed. We introduce an automated assessment of the SCPT based on inertial measurement units (IMU) in a study of 83 participants aged 70-87 years. For power evaluations of the lower extremities, the activity of climbing stairs was automatically classified via machine learning and the power was calculated based on the test duration and covered height. Climbing stairs was correctly classified in 93% of the cases. We also achieved a good correlation of the power calculations with the conventional stop watc h measurements with a mean deviation of 2.35%. The system’s sensitivity to detect the transition towards frailty has been confirmed. Furthermore, we discussed the general suitability of the automated stair climb power algorithm in unsupervised, standardized home-assessments. (More)

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Paper citation in several formats:
Hellmers, S.; Kromke, T.; Dasenbrock , L.; Heinks, A.; Bauer, J.; Hein, A. and Fudickar, S. (2018). Stair Climb Power Measurements via Inertial Measurement Units - Towards an Unsupervised Assessment of Strength in Domestic Environments.In Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, ISBN 978-989-758-281-3, pages 39-47. DOI: 10.5220/0006543900390047

@conference{healthinf18,
author={Sandra Hellmers. and Tobias Kromke. and Lena Dasenbrock . and Andrea Heinks. and Jürgen M. Bauer. and Andreas Hein. and Sebastian Fudickar.},
title={Stair Climb Power Measurements via Inertial Measurement Units - Towards an Unsupervised Assessment of Strength in Domestic Environments},
booktitle={Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF,},
year={2018},
pages={39-47},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006543900390047},
isbn={978-989-758-281-3},
}

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF,
TI - Stair Climb Power Measurements via Inertial Measurement Units - Towards an Unsupervised Assessment of Strength in Domestic Environments
SN - 978-989-758-281-3
AU - Hellmers, S.
AU - Kromke, T.
AU - Dasenbrock , L.
AU - Heinks, A.
AU - Bauer, J.
AU - Hein, A.
AU - Fudickar, S.
PY - 2018
SP - 39
EP - 47
DO - 10.5220/0006543900390047

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