scholarly journals Distribution and motor ability of children with cerebral palsy in Scotland: a registry analysis

2018 ◽  
Vol 64 (1) ◽  
pp. 16-21 ◽  
Author(s):  
Kate E Bugler ◽  
Mark S Gaston ◽  
James E Robb

Background and aims Cerebral palsy is the commonest long-term physical disability in children with a prevalence of between 1.77 and 2.11/1000 live births. In 2013, the Cerebral Palsy Integrated Pathway Scotland (CPIPS) surveillance programme was introduced in all 14 Health Boards in Scotland and provides a standardised musculoskeletal examination of the spine and lower limbs. The purpose of this study was to report the prevalence, subtypes, motor classification and motor ability of children with cerebral palsy in Scotland. Methods and results The family/carer’s postal address, the child’s neurological classification, motor subtypes, Gross Motor Functional Classification (GMFCS) Level and Functional Mobility Scale of 1972 children at first registration in CPIPS 2013–2018 were analysed. Their mean age at first assessment was 7.6 years. There was an overall prevalence of cerebral palsy in Scotland of 2.02/1000. GMFCS levels and Functional Mobility Scale data and prevalence were reported by Health Board and were comparable to that reported elsewhere. Conclusion For the first time, data are available on the motor abilities of the total population of children with cerebral palsy in Scotland. This information will be highly relevant to resource management of current and future motor needs of these children.

2021 ◽  
Vol 70 ◽  
pp. 115-128
Author(s):  
Jie Li ◽  
Zhelong Wang ◽  
Sen Qiu ◽  
Hongyu Zhao ◽  
Jiaxin Wang ◽  
...  

2019 ◽  
Vol 6 (11) ◽  
pp. 191011 ◽  
Author(s):  
Ryan Cunningham ◽  
María B. Sánchez ◽  
Penelope B. Butler ◽  
Matthew J. Southgate ◽  
Ian D. Loram

The aim of this study was to provide automated identification of postural point-features required to estimate the location and orientation of the head, multi-segmented trunk and arms from videos of the clinical test ‘Segmental Assessment of Trunk Control’ (SATCo). Three expert operators manually annotated 13 point-features in every fourth image of 177 short (5–10 s) videos (25 Hz) of 12 children with cerebral palsy (aged: 4.52 ± 2.4 years), participating in SATCo testing. Linear interpolation for the remaining images resulted in 30 825 annotated images. Convolutional neural networks were trained with cross-validation, giving held-out test results for all children. The point-features were estimated with error 4.4 ± 3.8 pixels at approximately 100 images per second. Truncal segment angles (head, neck and six thoraco-lumbar–pelvic segments) were estimated with error 6.4 ± 2.8°, allowing accurate classification ( F 1 > 80%) of deviation from a reference posture at thresholds up to 3°, 3° and 2°, respectively. Contact between arm point-features (elbow and wrist) and supporting surface was classified at F 1 = 80.5%. This study demonstrates, for the first time, technical feasibility to automate the identification of (i) a sitting segmental posture including individual trunk segments, (ii) changes away from that posture, and (iii) support from the upper limb, required for the clinical SATCo.


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