An anomaly detection technique in wearable wireless monitoring systems for studies of gait freezing in Parkinson's disease

Thuy T. Pham*, Diep N. Nguyen, Eryk Dutkiewicz, Alistair L. McEwan, Philip H. W. Leong

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

4 Citations (Scopus)

Abstract

Wearable monitoring systems have been in need for studies of gaits especially freezing of gait detection in patients with Parkinson's disease. The causality of gait freezing is still not fully understood. The histogram of gait freezing is the key assessment of the disease, thus monitoring them in patients' daily life is much appreciated. A real-Time signal processing platform for wearable sensors can help record freezing time instances. However, current monitor systems are calibrated with offline training (patient-dependent) that is cumbersome and time-consuming. In this work, by using acceleration data and spectral analysis, we propose an online/real-Time detection technique. Periods of low acceleration and low spectral coherence are identified and patient-independent parameters are then extracted. Using this set of new features, we validated our method by comparing it with clinicians' labels. The proposed approach achieved an overall mean (±SD) sensitivity (specificity) of 87 ± 0.3% (94±0.3%). To our best knowledge, this is the best performance for automated subject-independent approaches.

Original languageEnglish
Title of host publicationThe 31st International Conference on Information Networking (ICOIN 2017)
Subtitle of host publicationproceedings
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages41-45
Number of pages5
ISBN (Electronic)9781509051243
ISBN (Print)9781509051250
DOIs
Publication statusPublished - 2017
Externally publishedYes
Event31st International Conference on Information Networking, ICOIN 2017 - Da Nang, Viet Nam
Duration: 11 Jan 201713 Jan 2017

Other

Other31st International Conference on Information Networking, ICOIN 2017
CountryViet Nam
CityDa Nang
Period11/01/1713/01/17

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