title: Pelvis feature extraction and classification of Cardiff body match rig base measurements for input into a knowledge-based system.
abstract: The purpose of this paper is to determine whether it is possible to use an automated measurement tool to clinically classify clients who are wheelchair users with severe musculoskeletal deformities, replacing the current process which relies upon clinical engineers with advanced knowledge and skills. Clients' body shapes were captured using the Cardiff Body Match (CBM) Rig developed by the Rehabilitation Engineering Unit (REU) at Rookwood Hospital in Cardiff. A bespoke feature extraction algorithm was developed that estimates the position of external landmarks on clients' pelvises so that useful measurements can be obtained. The outputs of the feature extraction algorithms were compared to CBM measurements where the positions of the client's pelvis landmarks were known. The results show that using the extracted features facilitated classification. Qualitative analysis showed that the estimated positions of the landmark points were close enough to their actual positions to be useful to clinicians undertaking clinical assessments.
authors.affiliation: Faculty of Advanced Technology, University of Glamorgan, Pontypridd CF37 1DL, UK. ajpartlo@glam.ac.uk
authors.forename: Adam
authors.initials: A
authors.lastname: Partlow
authors.forename: Colin
authors.initials: C
authors.lastname: Gibson
authors.forename: Janusz
authors.initials: J
authors.lastname: Kulon
authors.forename: Ian
authors.initials: I
authors.lastname: Wilson
authors.forename: Steven
authors.initials: S
authors.lastname: Wilcox
mesh_terms: D000465:Algorithms; D000886:Anthropometry / Q000379:methods*; D001698:Biomedical Engineering; D016208:Databases, Factual; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D051188:Knowledge Bases; D009140:Musculoskeletal Diseases / Q000473:pathology; D010388:Pelvis / Q000033:anatomy & histology*; D011187:Posture; D014910:Wheelchairs