Picture of server farm and IT infrastructure

Where technology & law meet: Open Access research on data security & its regulation ...

Strathprints makes available Open Access scholarly outputs exploring both the technical aspects of computer security, but also the regulation of existing or emerging technologies. A research specialism of the Department of Computer & Information Sciences (CIS) is computer security. Researchers explore issues surrounding web intrusion detection techniques, malware characteristics, textual steganography and trusted systems. Digital forensics and cyber crime are also a focus.

Meanwhile, the School of Law and its Centre for Internet Law & Policy undertake studies on Internet governance. An important component of this work is consideration of privacy and data protection questions and the increasing focus on cybercrime and 'cyberterrorism'.

Explore the Open Access research by CIS on computer security or the School of Law's work on law, technology and regulation. Or explore all of Strathclyde's Open Access research...

Strathprints

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.

[img]
Preview
 Text (Yang-IEEEA2016-human-upper-limb-motion-analysis-for-post-stroke-impairment-assessment)
Yang_IEEEA2016_human_upper_limb_motion_analysis_for_post_stroke_impairment_assessment.pdf
Accepted Author Manuscript
Download (14MB) | Preview

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.

Item type: Article
ID code: 55526
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: 21 May 2018 09:40
Related URLs:
URI: https://strathprints.strath.ac.uk/id/eprint/55526
Export data:
CORE (COnnecting REpositories)