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Data mining in medicine: relationship of scoliotic spine curvature to the movement sequence of lateral bending positions

Version 2 2024-06-12, 18:40
Version 1 2019-05-22, 11:38
conference contribution
posted on 2024-06-12, 18:40 authored by A Jalalian, FEH Tay, G Liu
We aim to determine relationships between scoliotic spine curvatures in movement sequence from left bending to erect to right bending positions in the frontal plane. A multi-body kinematic modelling approach is utilized to reconstruct the curvatures and study the relationships. The spine is considered as a chain of micro-scale motion-segments (MMSs). Linear regression method is adopted to identify relationships between angles of MMSs in erect and lateral bending positions. Excellent linear relationships (R2 = 0.93 ± 0.09) were identified between angles of MMSs placed between each two successive vertebrae. We showed that these relationships give good estimates of the curvatures (Root-mean-square-error = 0.0172 ± 0.0114 mm) and the key parameters for scoliosis surgery planning; estimation errors for Cobb angle, spinal mobility, and flexibility were 0.0016 ± 0.0122°, 0.0010 ± 0.086°, and 0.0002 ± 0.0002 respectively. This paper provides an important insight: scoliotic spine curvatures in lateral bending positions and the key parameters for surgery planning can be predicted using spine curvature in erect position.

History

Volume

9728

Pagination

29-40

Location

New York, N.Y.

Start date

2016-07-13

End date

2016-07-17

ISSN

0302-9743

eISSN

1611-3349

ISBN-13

9783319415604

Language

eng

Publication classification

E1.1 Full written paper - refereed

Copyright notice

2016, Springer International Publishing Switzerland

Editor/Contributor(s)

Perner P

Title of proceedings

ICDM 2016 : Proceedings of the 16th Industrial Conference on Data Mining 2016

Event

Data Mining. Conference (16th : 2016 : New York, N.Y.)

Publisher

Springer

Place of publication

Cham, Switzerland

Series

Data Mining Conference

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