TY - JOUR
T1 - Clinical use of prediction regions for motion analysis
AU - Sutherland, David H.
AU - Kaufman, Kenton R.
AU - Campbell, Karen
AU - Ambrosini, Diane
AU - Wyatt, Marilynn
PY - 1996/9
Y1 - 1996/9
N2 - 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.
AB - 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.
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U2 - 10.1111/j.1469-8749.1996.tb15111.x
DO - 10.1111/j.1469-8749.1996.tb15111.x
M3 - Article
C2 - 8810708
AN - SCOPUS:0029812533
SN - 0012-1622
VL - 38
SP - 773
EP - 781
JO - Developmental Medicine and Child Neurology
JF - Developmental Medicine and Child Neurology
IS - 9
ER -