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Freezing of gait detection in Parkinson's Disease: A subject-independent detector using anomaly scores

journal contribution
posted on 22.05.2018, 00:00 by TT Pham, Steven MooreSteven Moore, SJG Lewis, DN Nguyen, E Dutkiewicz, AJ Fuglevand, AL McEwan, PHW Leong
© 2012 IEEE. Freezing of gait (FoG) is common in Parkinsonian gait and strongly relates to falls. Current clinical FoG assessments are patients' self-report diaries and experts' manual video analysis. Both are subjective and yield moderate reliability. Existing detection algorithms have been predominantly designed in subject-dependent settings. In this paper, we aim to develop an automated FoG detector for subject independent. After extracting highly relevant features, we apply anomaly detection techniques to detect FoG events. Specifically, feature selection is performed using correlation and clusterability metrics. From a list of 244 feature candidates, 36 candidates were selected using saliency and robustness criteria. We develop an anomaly score detector with adaptive thresholding to identify FoG events. Then, using accuracy metrics, we reduce the feature list to seven candidates. Our novel multichannel freezing index was the most selective across all window sizes, achieving sensitivity (specificity) of 96% (79%). On the other hand, freezing index from the vertical axis was the best choice for a single input, achieving sensitivity (specificity) of 94% (84%) for ankle and 89% (94%) for back sensors. Our subject-independent method is not only significantly more accurate than those previously reported, but also uses a much smaller window (e.g., 3 s versus 7.5 s) and/or lower tolerance (e.g., 0.4 s versus 2 s).

History

Volume

64

Issue

11

Start Page

2719

End Page

2728

Number of Pages

10

eISSN

1558-2531

ISSN

0018-9294

Publisher

Institute of Electrical and Electronics Engineers

Peer Reviewed

Yes

Open Access

No

Acceptance Date

23/01/2017

External Author Affiliations

University of Technology; University of Arizona; The University of Sydney

Era Eligible

Yes

Journal

IEEE Transactions on Biomedical Engineering

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