Staffordshire University logo
STORE - Staffordshire Online Repository

Clustering the Clusters –Knowledge Enhancing Tool for Diagnosing Elderly Falling Risk

Rueangsirarak, Worasak, ATKINS, Anthony, SHARP, Bernadette, Chakpitak, N and Meksamoot, M (2013) Clustering the Clusters –Knowledge Enhancing Tool for Diagnosing Elderly Falling Risk. International Journal of Healthcare Technology and Management (IJHTM), 14 (1-2). ISSN 1368-2156

Full text not available from this repository. (Request a copy)

Abstract or description

Falls which affect the musculoskeletal system are the leading cause of injury in people over 65 years. To address the growing problem of falls in an ageing society and to support and improve the healthcare service provided, a diagnostic tool is required. This study proposes a new approach to analyse and diagnose the risks associated with elderly falling by applying K-means clustering to cluster and assess the fall risks data of elderly Thai people, captured using motion capture technology. These clusters are mapped into two-dimensional space using self-organising map (SOM). The resulting 95.45% accuracy suggests that the two-stage clustering technique is applicable and useful in managing fall risks which can then be included in decision support system to assist physiotherapists, in recommending a customised rehabilitation programme.

Item Type: Article
Faculty: School of Computing and Digital Technologies > Computing
Depositing User: Prof Bernadette SHARP
Date Deposited: 18 Jun 2013 11:52
Last Modified: 24 Feb 2023 03:47

Actions (login required)

View Item View Item

DisabledGo Staffordshire University is a recognised   Investor in People. Sustain Staffs
Legal | Freedom of Information | Site Map | Job Vacancies
Staffordshire University, College Road, Stoke-on-Trent, Staffordshire ST4 2DE t: +44 (0)1782 294000