Clinical use of prediction regions for motion analysis

David H. Sutherland, Kenton R. Kaufman, Karen Campbell, Diane Ambrosini, Marilynn Wyatt

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

This study assesses the diagnostic capability of statistically defined prediction regions, developed by a 'bootstrap' method, for assessing the curves of angular rotation of joints in children as they walk. The prediction regions had been previously developed in the authors' laboratory from a study of 309 normal children. The goal of the present study was to determine whether these computer-generated prediction regions could be used as a screen in clinical gait analysis, to determine whether a movement falls outside the normal range of variability. Kinematic analysis of 38 consecutive children referred to the motion analysis laboratory for clinical gait assessment provided 912 curves of lower-extremity joint angle dynamics. An experienced observer first inspected the patients' curves with mean normal curves superimposed and designated the curves as normal or abnormal. The performance of the computer-generated prediction regions was judged by comparison with the experienced observer's designations. The prediction regions were found to have a high sensitivity (81%), indicating that they can be used as an initial screen to identify deficits in lower limb function.

Original languageEnglish (US)
Pages (from-to)773-781
Number of pages9
JournalDevelopmental Medicine and Child Neurology
Volume38
Issue number9
DOIs
StatePublished - Sep 1996

ASJC Scopus subject areas

  • Pediatrics, Perinatology, and Child Health
  • Developmental Neuroscience
  • Clinical Neurology

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