1. Statistical shape modelling versus linear scaling: Effects on predictions of hip joint centre location and muscle moment arms in people with hip osteoarthritis
- Author
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Jasvir S. Bahl, Thor F. Besier, Dominic Thewlis, Bryce A. Killen, John B. Arnold, David Lloyd, Lucian B. Solomon, Ju Zhang, Mark Taylor, Bahl, Jasvir S, Zhang, Ju, Killen, Bryce A, Taylor, Mark, Solomon, Lucian B, Arnold, John B, Lloyd, David G, Besier, Thor F, and Thewlis, Dominic
- Subjects
Adult ,Male ,Mean squared error ,0206 medical engineering ,Biomedical Engineering ,Biophysics ,02 engineering and technology ,Osteoarthritis, Hip ,03 medical and health sciences ,statistical shape model ,0302 clinical medicine ,Statistics ,Linear scale ,medicine ,Humans ,Orthopedics and Sports Medicine ,Muscle, Skeletal ,Joint (geology) ,Scaling ,Pelvis ,Mathematics ,Models, Statistical ,scaling ,Rehabilitation ,musculoskeletal modelling ,hip joint centre ,020601 biomedical engineering ,Regression ,Biomechanical Phenomena ,Moment (mathematics) ,Euclidean distance ,medicine.anatomical_structure ,Research Design ,Female ,Hip Joint ,Tomography, X-Ray Computed ,030217 neurology & neurosurgery - Abstract
Marker-based dynamic functional or regression methods are used to compute joint centre locations that can be used to improve linear scaling of the pelvis in musculoskeletal models, although large errors have been reported using these methods. This study aimed to investigate if statistical shape models could improve prediction of the hip joint centre (HJC) location. The inclusion of complete pelvis imaging data from computed tomography (CT) was also explored to determine if free-form deformation techniques could further improve HJC estimates. Mean Euclidean distance errors were calculated between HJC from CT and estimates from shape modelling methods, and functional- and regression-based linear scaling approaches. The HJC of a generic musculoskeletal model was also perturbed to compute the root-mean squared error (RMSE) of the hip muscle moment arms between the reference HJC obtained from CT and the different scaling methods. Shape modelling without medical imaging data significantly reduced HJC location error estimates (11.4 ± 3.3 mm) compared to functional (36.9 ± 17.5 mm, p =
- Published
- 2019
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