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

Athena Jalalian, Francis E.H. Tay*, Gabriel Liu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

2 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationAdvances in Data Mining: Applications and Theoretical Aspects
Subtitle of host publication16th Industrial Conference, ICDM 2016, New York, NY, USA, July 13-17, 2016: Proceedings
EditorsPetra Perner
Place of PublicationCham
PublisherSpringer Verlag
Pages29-40
Number of pages12
ISBN (Electronic)978-3-319-41561-1
ISBN (Print)978-3-319-41560-4
DOIs
Publication statusPublished - 1 Jan 2016
Externally publishedYes
Event16th Industrial Conference on Advances in Data Mining, ICDM 2016 - New York, United States
Duration: 13 Jul 201617 Jul 2016

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume9728
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349
NameLecture Notes in Artificial Intelligence
PublisherSpringer

Conference

Conference16th Industrial Conference on Advances in Data Mining, ICDM 2016
CountryUnited States
CityNew York
Period13/07/1617/07/16

Keywords

  • Adolescent idiopathic scoliosis
  • Lateral bending positions
  • Multi-body kinematic model
  • Spine curvature
  • Spine movement sequence

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