Towards holistic free-living assessment in Parkinson's disease: Unification of gait and fall algorithms with a single accelerometer

Godfrey, Alan, Bourke, Alan, Del Din, Silvia, Morris, Rosie, Hickey, Aodhan, Helbostad, Jorunn L and Rochester, Lynn (2016) Towards holistic free-living assessment in Parkinson's disease: Unification of gait and fall algorithms with a single accelerometer. In: 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 17th - 20th August 2016, Orlando, Florida.

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Abstract

Technological developments have seen the miniaturization of sensors, small enough to be embedded in wearable devices facilitating unobtrusive and longitudinal monitoring in free-living environments. Concurrently, the advances in algorithms have been ad-hoc and fragmented. To advance the mainstream use of wearable technology and improved functionality of algorithms all methodologies must be unified and robustly tested within controlled and free-living conditions. Here we present and unify a (i) gait segmentation and analysis algorithm and (ii) a fall detection algorithm. We tested the unified algorithms on a cohort of young healthy adults within a laboratory. We then deployed the algorithms on longitudinal (7 day) accelerometer-based data from an older adult with Parkinson's disease (PD) to quantify real world gait and falls. We compared instrumented falls to a self-reported falls diary to test algorithm efficiency and discuss the use of unified algorithms to impact free-living assessment in PD where accurate recognition of gait may reduce the number of automated detected falls (38/week). This informs ongoing work to use gait and related outcomes as pragmatic clinical markers.

Item Type:	Conference or Workshop Item (Paper)
Subjects:	B900 Others in Subjects allied to Medicine G400 Computer Science
Department:	Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User:	Paul Burns
Date Deposited:	20 Apr 2018 14:37
Last Modified:	11 Oct 2019 21:03
URI:	http://nrl.northumbria.ac.uk/id/eprint/34059

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