Accelerometer-based gait assessment: Pragmatic deployment on an international scale

Del Din, Silvia, Hickey, Aodhan, Woodman, Simon, Hiden, Hugo, Morris, Rosie, Watson, Paul, Nazarpour, Kianoush, Catt, Michael, Rochester, Lynn and Godfrey, Alan (2016) Accelerometer-based gait assessment: Pragmatic deployment on an international scale. In: 2016 IEEE Statistical Signal Processing Workshop (SSP). IEEE. ISBN 978-1-4673-7804-8

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Official URL: https://doi.org/10.1109/SSP.2016.7551794

Abstract

Gait is emerging as a powerful tool to detect early disease and monitor progression across a number of pathologies. Typically quantitative gait assessment has been limited to specialised laboratory facilities. However, measuring gait in home and community settings may provide a more accurate reflection of gait performance because: (1) it will not be confounded by attention which may be heightened during formal testing; and (2) it allows performance to be captured over time. This work addresses the feasibility and challenges of measuring gait characteristics with a single accelerometer based wearable device during free-living activity. Moreover, it describes the current methodological and statistical processes required to quantify those sensitive surrogate markers for ageing and pathology. A unified framework for large scale analysis is proposed. We present data and workflows from healthy older adults and those with Parkinson's disease (PD) while presenting current algorithms and scope within modern pervasive healthcare. Our findings suggested that free-living conditions heighten between group differences showing greater sensitivity to PD, and provided encouraging results to support the use of the suggested framework for large clinical application.

Item Type: Book Section
Uncontrolled Keywords: wearable technology, Accelerometer, free-living gait, Parkinson's disease
Subjects: B900 Others in Subjects allied to Medicine
G900 Others in Mathematical and Computing Sciences
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Becky Skoyles
Date Deposited: 20 Apr 2018 14:50
Last Modified: 20 Apr 2018 14:50
URI: http://nrl.northumbria.ac.uk/id/eprint/34062

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