In this study a generalised dynamic neural network (GDNN) was designed to process gait analysis parameters to evaluate equinus deformity in ambulatory children with cerebral palsy. The aim was to differentiate dynamic calf muscle tightness from fixed muscle contracture. Patients underwent clinical examination and had instrumented gait analysis before evaluating their equinus under anaesthesia and muscle relaxation at the time of surgery to improve gait. The performance of the clinical examination, the subjective interpretation of gait analysis results, and the application of the neural network to assess ankle function were compared to the examination under anaesthesia. Evaluation of equinus by a Neural Network showed high sensitivity and specificity values with a likelihood ratio of +14.63. The results indicate that dynamic calf muscle tightness can be differentiated from fixed calf muscle contracture with considerable precision that might facilitate clinical decision-making.
%0 Journal Article
%1 Zwick2004
%A Zwick, Ernst B
%A Leistritz, Lutz
%A Milleit, Berko
%A Saraph, Vinay
%A Zwick, Gertrude
%A Galicki, Miroslaw
%A Witte, Herbert
%A Steinwender, Gerhardt
%D 2004
%J Gait Posture
%K Algorithms; Anes; Ankle; Biomechanics; Cerebral Palsy; Child; Equinus Deformity; Gait; Humans; Knee; Muscles; Neural Networks (Computer); Pelvis; Retrospective Studies; Walking; thesia
%N 3
%P 273--279
%R 10.1016/j.gaitpost.2003.10.002
%T Classification of equinus in ambulatory children with cerebral palsy-discrimination between dynamic tightness and fixed contracture.
%U http://dx.doi.org/10.1016/j.gaitpost.2003.10.002
%V 20
%X In this study a generalised dynamic neural network (GDNN) was designed to process gait analysis parameters to evaluate equinus deformity in ambulatory children with cerebral palsy. The aim was to differentiate dynamic calf muscle tightness from fixed muscle contracture. Patients underwent clinical examination and had instrumented gait analysis before evaluating their equinus under anaesthesia and muscle relaxation at the time of surgery to improve gait. The performance of the clinical examination, the subjective interpretation of gait analysis results, and the application of the neural network to assess ankle function were compared to the examination under anaesthesia. Evaluation of equinus by a Neural Network showed high sensitivity and specificity values with a likelihood ratio of +14.63. The results indicate that dynamic calf muscle tightness can be differentiated from fixed calf muscle contracture with considerable precision that might facilitate clinical decision-making.
@article{Zwick2004,
abstract = {In this study a generalised dynamic neural network (GDNN) was designed to process gait analysis parameters to evaluate equinus deformity in ambulatory children with cerebral palsy. The aim was to differentiate dynamic calf muscle tightness from fixed muscle contracture. Patients underwent clinical examination and had instrumented gait analysis before evaluating their equinus under anaesthesia and muscle relaxation at the time of surgery to improve gait. The performance of the clinical examination, the subjective interpretation of gait analysis results, and the application of the neural network to assess ankle function were compared to the examination under anaesthesia. Evaluation of equinus by a Neural Network showed high sensitivity and specificity values with a likelihood ratio of +14.63. The results indicate that dynamic calf muscle tightness can be differentiated from fixed calf muscle contracture with considerable precision that might facilitate clinical decision-making.},
added-at = {2014-07-20T09:31:15.000+0200},
author = {Zwick, Ernst B and Leistritz, Lutz and Milleit, Berko and Saraph, Vinay and Zwick, Gertrude and Galicki, Miroslaw and Witte, Herbert and Steinwender, Gerhardt},
biburl = {https://www.bibsonomy.org/bibtex/29519ce91f87f8681676ac6800c182407/ar0berts},
doi = {10.1016/j.gaitpost.2003.10.002},
groups = {public},
interhash = {69a74dd7e25da4269bb765f174eb9e07},
intrahash = {9519ce91f87f8681676ac6800c182407},
journal = {Gait Posture},
keywords = {Algorithms; Anes; Ankle; Biomechanics; Cerebral Palsy; Child; Equinus Deformity; Gait; Humans; Knee; Muscles; Neural Networks (Computer); Pelvis; Retrospective Studies; Walking; thesia},
month = Dec,
number = 3,
pages = {273--279},
pii = {S0966636203001723},
pmid = {15531174},
timestamp = {2014-07-20T09:31:15.000+0200},
title = {Classification of equinus in ambulatory children with cerebral palsy-discrimination between dynamic tightness and fixed contracture.},
url = {http://dx.doi.org/10.1016/j.gaitpost.2003.10.002},
username = {ar0berts},
volume = 20,
year = 2004
}