Literature DB >> 24485513

Prediction bands and intervals for the scapulo-humeral coordination based on the Bootstrap and two Gaussian methods.

A G Cutti1, I Parel2, M Raggi3, E Petracci4, A Pellegrini5, A P Accardo6, R Sacchetti3, G Porcellini7.   

Abstract

Quantitative motion analysis protocols have been developed to assess the coordination between scapula and humerus. However, the application of these protocols to test whether a subject's scapula resting position or pattern of coordination is "normal", is precluded by the unavailability of reference prediction intervals and bands, respectively. The aim of this study was to present such references for the "ISEO" protocol, by using the non-parametric Bootstrap approach and two parametric Gaussian methods (based on Student's T and Normal distributions). One hundred and eleven asymptomatic subjects were divided into three groups based on their age (18-30, 31-50, and 51-70). For each group, "monolateral" prediction bands and intervals were computed for the scapulo-humeral patterns and the scapula resting orientation, respectively. A fourth group included the 36 subjects (42 ± 13 year-old) for whom the scapulo-humeral coordination was measured bilaterally, and "differential" prediction bands and intervals were computed, which describe right-to-left side differences. Bootstrap and Gaussian methods were compared using cross-validation analyses, by evaluating the coverage probability in comparison to a 90% target. Results showed a mean coverage for Bootstrap from 86% to 90%, compared to 67-70% for parametric bands and 87-88% for parametric intervals. Bootstrap prediction bands showed a distinctive change in amplitude and mean pattern related to age, with an increase toward scapula retraction, lateral rotation and posterior tilt. In conclusion, Bootstrap ensures an optimal coverage and should be preferred over parametric methods. Moreover, the stratification of "monolateral" prediction bands and intervals by age appears relevant for the correct classification of patients.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Bootstrap; Motion analysis; Prediction; Scapular kinematics; Shoulder

Mesh:

Year:  2014        PMID: 24485513     DOI: 10.1016/j.jbiomech.2013.12.028

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  8 in total

1.  Can posterior capsular stretching rehabilitation protocol change scapula kinematics in asymptomatic baseball pitchers?

Authors:  A Pellegrini; P Tonino; D Salazar; K Hendrix; I Parel; A Cutti; P Paladini; F Ceccarelli; G Porcellini
Journal:  Musculoskelet Surg       Date:  2016-11-30

2.  Assessment of anatomical and reverse total shoulder arthroplasty with the scapula-weighted Constant-Murley score.

Authors:  Giovanni Merolla; Ilaria Parel; Andrea Giovanni Cutti; Maria Vittoria Filippi; Paolo Paladini; Giuseppe Porcellini
Journal:  Int Orthop       Date:  2018-08-10       Impact factor: 3.075

3.  Glenohumeral and scapulohumeral kinematic analysis of patients with traumatic anterior instability wearing a shoulder brace: a prospective laboratory study.

Authors:  F Dellabiancia; I Parel; M V Filippi; G Porcellini; G Merolla
Journal:  Musculoskelet Surg       Date:  2017-07-29

4.  The latissimus dorsi tendon functions as an external rotator after arthroscopic-assisted transfer for massive irreparable posterosuperior rotator cuff tears.

Authors:  Olimpio Galasso; Matteo Mantovani; Marco Muraccini; Antonella Berardi; Massimo De Benedetto; Nicola Orlando; Giorgio Gasparini; Roberto Castricini
Journal:  Knee Surg Sports Traumatol Arthrosc       Date:  2019-12-06       Impact factor: 4.342

5.  Evaluation of a novel portable three-dimensional scapular kinematics assessment system with inter and intraobserver reproducibility and normative data for healthy adults.

Authors:  Miguel Angel Ruiz Ibán; Andrea Paniagua Gonzalez; Marco Muraccini; Cristina Asenjo Gismero; Alessandro Varini; Antonella Berardi; Matteo Mantovani
Journal:  J Exp Orthop       Date:  2020-05-13

6.  Definition of anatomical zero positions for assessing shoulder pose with 3D motion capture during bilateral abduction of the arms.

Authors:  Oliver Rettig; Britta Krautwurst; Michael W Maier; Sebastian I Wolf
Journal:  BMC Musculoskelet Disord       Date:  2015-12-09       Impact factor: 2.362

7.  A survey of human shoulder functional kinematic representations.

Authors:  Rakesh Krishnan; Niclas Björsell; Elena M Gutierrez-Farewik; Christian Smith
Journal:  Med Biol Eng Comput       Date:  2018-10-26       Impact factor: 2.602

8.  Effects of Internal Fixation for Mid-Shaft Clavicle Fractures on Shoulder Kinematics During Humeral Elevations.

Authors:  Li-Wei Hung; Hsuan-Yu Lu; Chung-Hsun Chang; Tsan-Yang Chen; Ting-Ming Wang; Tung-Wu Lu
Journal:  Front Bioeng Biotechnol       Date:  2021-07-22
  8 in total

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