Human upper limb motion analysis for post-stroke impairment assessment using video analytics

Yang, Cheng and Kerr, Andrew and Stankovic, Vladimir and Stankovic, Lina and Rowe, Philip and Cheng, Samuel (2016) Human upper limb motion analysis for post-stroke impairment assessment using video analytics. IEEE Access, 4. pp. 650-659.

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    Abstract

    Stroke is a worldwide healthcare problem which often causes long-term motor impairment, handicap, and disability. Optical motion analysis systems are commonly used for impairment assessment due to high accuracy. However, the requirement of equipment-heavy and large laboratory space together with operational expertise, makes these systems impractical for local clinic and home use. We propose an alternative, cost-effective and portable, decision support system for optical motion analysis, using a single camera. The system relies on detecting and tracking markers attached to subject's joints, data analytics for calculating relevant rehabilitation parameters, visualization, and robust classification based on graph-based signal processing. Experimental results show that the proposed decision support system has the potential to offer stroke survivors and clinicians an alternative, affordable, accurate and convenient impairment assessment option suitable for home healthcare and tele-rehabilitation.

    ORCID iDs

    Yang, Cheng ORCID logoORCID: https://orcid.org/0000-0002-3540-1598, Kerr, Andrew ORCID logoORCID: https://orcid.org/0000-0002-7666-9283, Stankovic, Vladimir ORCID logoORCID: https://orcid.org/0000-0002-1075-2420, Stankovic, Lina ORCID logoORCID: https://orcid.org/0000-0002-8112-1976, Rowe, Philip ORCID logoORCID: https://orcid.org/0000-0002-4877-8466 and Cheng, Samuel;
    • Item type:Article
      ID code:55526
      Dates:
      Date
      Event
      10 March 2016
      Published
      1 February 2016
      Published Online
      18 January 2016
      Accepted
      Notes:© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
      Keywords:rehabilitation, video analytics, graph-based signal processing, Engineering (General). Civil engineering (General), Engineering(all)
      Subjects:Technology > Engineering (General). Civil engineering (General)
      Department:Faculty of Engineering > Electronic and Electrical Engineering
      Faculty of Engineering > Biomedical Engineering
      Depositing user: Pure Administrator
      Date deposited:11 Feb 2016 10:00
      Last modified:17 Apr 2021 00:30
      Related URLs:
      URI:https://strathprints.strath.ac.uk/id/eprint/55526
    CORE (COnnecting REpositories)