Please use this identifier to cite or link to this item:
|Title:||Clustering the clusters - Knowledge enhancing tool for diagnosing elderly falling risk|
Anthony S. Atkins
|Abstract:||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. Copyright © 2013 Inderscience Enterprises Ltd.|
|Appears in Collections:||CMUL: Journal Articles|
Files in This Item:
There are no files associated with this item.
Items in CMUIR are protected by copyright, with all rights reserved, unless otherwise indicated.