Intelligent wearable system with accurate detection of abnormal gait and timely cueing for mobility enhancement of people with Parkinson's disease

Bao Yang, Ying Li, Fei Wang, Stephanie Auyeung, Manyui Leung, Margaret Mak, Xiaoming Tao

Research output: Journal article publicationJournal articleAcademic researchpeer-review

3 Citations (Scopus)

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.

Original languageEnglish
Article numbere12
JournalWearable Technologies
Volume3
DOIs
Publication statusPublished - 28 Jun 2022

Keywords

  • freezing of gait
  • intelligent wearable system
  • multisensory cueing
  • real-time detection

ASJC Scopus subject areas

  • Biomedical Engineering
  • Rehabilitation
  • Human-Computer Interaction

Fingerprint

Dive into the research topics of 'Intelligent wearable system with accurate detection of abnormal gait and timely cueing for mobility enhancement of people with Parkinson's disease'. Together they form a unique fingerprint.

Cite this