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Turning detection during gait - Algorithm validation and influence of sensor location and turning characteristics in the classification of Parkinson’s disease.pdf
Published (Version of Record)CC BY V4.0, Open Access
Journal article
Turning detection during gait: Algorithm validation and influence of sensor location and turning characteristics in the classification of Parkinson’s disease
Sensors, Vol.20(18), Article 5377
2020
Abstract
Parkinson’s disease (PD) is a common neurodegenerative disorder resulting in a range of mobility deficits affecting gait, balance and turning. In this paper, we present: (i) the development and validation of an algorithm to detect turns during gait; (ii) a method to extract turn characteristics; and (iii) the classification of PD using turn characteristics. Thirty-seven people with PD and 56 controls performed 180-degree turns during an intermittent walking task. Inertial measurement units were attached to the head, neck, lower back and ankles. A turning detection algorithm was developed and validated by two raters using video data. Spatiotemporal and signal-based characteristics were extracted and used for PD classification. There was excellent absolute agreement between the rater and the algorithm for identifying turn start and end (ICC ≥ 0.99). Classification modeling (partial least square discriminant analysis (PLS-DA)) gave the best accuracy of 97.85% when trained on upper body and ankle data. Balanced sensitivity (97%) and specificity (96.43%) were achieved using turning characteristics from the neck, lower back and ankles. Turning characteristics, in particular angular velocity, duration, number of steps, jerk and root mean square distinguished mild-moderate PD from controls accurately and warrant future examination as a marker of mobility impairment and fall risk in PD.
Details
- Title
- Turning detection during gait: Algorithm validation and influence of sensor location and turning characteristics in the classification of Parkinson’s disease
- Authors/Creators
- R.Z.U. Rehman (Author/Creator) - Newcastle UniversityP. Klocke (Author/Creator) - Newcastle Hospitals - Campus for Ageing and VitalityS. Hryniv (Author/Creator) - Newcastle Hospitals - Campus for Ageing and VitalityB. Galna (Author/Creator) - Newcastle UniversityL. Rochester (Author/Creator) - Newcastle UniversityS. Del Din (Author/Creator) - Newcastle UniversityL. Alcock (Author/Creator) - Newcastle University
- Publication Details
- Sensors, Vol.20(18), Article 5377
- Publisher
- MDPI
- Identifiers
- 991005541879007891
- Copyright
- © 2020 by the authors
- Murdoch Affiliation
- Murdoch University
- Language
- English
- Resource Type
- Journal article
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Source: InCites
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InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Collaboration types
- Domestic collaboration
- Citation topics
- 1 Clinical & Life Sciences
- 1.82 Gait & Posture
- 1.82.263 Gait and Balance
- Web Of Science research areas
- Chemistry, Analytical
- Engineering, Electrical & Electronic
- Instruments & Instrumentation
- ESI research areas
- Chemistry