Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/93494
DC Field | Value | Language |
---|---|---|
dc.contributor | School of Fashion and Textiles | en_US |
dc.contributor | Department of Rehabilitation Sciences | en_US |
dc.creator | Yang, B | en_US |
dc.creator | Li, Y | en_US |
dc.creator | Wang, F | en_US |
dc.creator | Auyeung, S | en_US |
dc.creator | Leung, M | en_US |
dc.creator | Mak, M | en_US |
dc.creator | Tao, X | en_US |
dc.date.accessioned | 2022-07-06T09:23:34Z | - |
dc.date.available | 2022-07-06T09:23:34Z | - |
dc.identifier.uri | http://hdl.handle.net/10397/93494 | - |
dc.language.iso | en | en_US |
dc.publisher | Cambridge University Press | en_US |
dc.rights | © Hong Kong Polytechnic University, 2022. Published by Cambridge University Press. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited. | en_US |
dc.rights | The following publication Yang, B., Li, Y., Wang, F., Auyeung, S., Leung, M., Mak, M., & Tao, X. (2022). Intelligent wearable system with accurate detection of abnormal gait and timely cueing for mobility enhancement of people with Parkinson’s disease. Wearable Technologies, 3, e12 is available at https://doi.org/10.1017/wtc.2022.9. | en_US |
dc.subject | Freezing of gait | en_US |
dc.subject | Intelligent wearable system | en_US |
dc.subject | Multisensory cueing | en_US |
dc.subject | Real-time detection | en_US |
dc.title | Intelligent wearable system with accurate detection of abnormal gait and timely cueing for mobility enhancement of people with Parkinson’s disease | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.volume | 3 | en_US |
dc.identifier.doi | 10.1017/wtc.2022.9 | en_US |
dcterms.abstract | Previously reported wearable systems for people with Parkinson’s disease (PD) have been focused on the detection of abnormal gait. They suffered from limited accuracy, large latency, poor durability, comfort, and convenience for daily use. Herewith we report an intelligent wearable system (IWS) that can accurately detect abnormal gait in real-time and provide timely cueing for PD patients. The system features novel sensitive, comfortable and durable plantar pressure sensing insoles with a highly compressed data set, an accurate and fast gait algorithm, and wirelessly controlled timely sensory cueing devices. A total of 29 PD patients participated in the first phase without cueing for developing processes of the algorithm, which achieved an accuracy of over 97% for off-line detection of freezing of gait (FoG). In the second phase with cueing, the evaluation of the whole system was conducted with 16 PD subjects via trial and a questionnaire survey. This system demonstrated an accuracy of 94% for real-time detection of FoG and a mean latency of 0.37 s between the onset of FoG and cueing activation. In questionnaire survey, 88% of the PD participants confirmed that this wearable system could effectively enhance walking, 81% thought that the system was comfortable and convenient, and 70% overcame the FoG. Therefore, the IWS makes it an effective, powerful, and convenient tool for enhancing the mobility of people with PD. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Wearable technologies, 2022, v. 3, e12 | en_US |
dcterms.isPartOf | Wearable technologies | en_US |
dcterms.issued | 2022 | - |
dc.identifier.eissn | 2631-7176 | en_US |
dc.identifier.artn | e12 | en_US |
dc.description.validate | 202207 bckw | en_US |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_TA | - |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | National Key R&D Program of China; Innovation and Technology Commission via Hong Kong Research Institute of Textiles and Apparel Ltd.; Hong Kong Polytechnic University | en_US |
dc.description.pubStatus | Published | en_US |
dc.description.TA | CUP (2022) | en_US |
dc.description.oaCategory | TA | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
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Yang_Intelligent_Wearable_System.pdf | 1.73 MB | Adobe PDF | View/Open |
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