A time-frequency based electromyographic analysis technique for use in cerebral palsy.
Surface electromyography (sEMG) is part of an instrumented gait assessment, however, the interpretation of the data in a clinically meaningful manner is often limited to the extraction of individual sEMG characteristics. The purpose of this study was to develop an assessment methodology using sEMG time and frequency characteristics extracted using wavelet analyses to provide clinically relevant information in children with cerebral palsy (CP). A retrospective study was conducted with 37 children (16 children with typical development (TD) and 21 children with spastic CP). sEMG signals were examined from selected musculature of the lower extremities during level ground walking. Wavelet analysis techniques, along with functional principal component analyses, were employed to calculate a sEMG index. The data indicated a grouping in the EMG index based on the level of motor impairment and the clinical diagnosis of spastic hemiplegia or diplegia. Further analyses of the index exhibited moderate to high (r=-0.43 to -0.74 and r=0.62-0.65) correlations with the existing gait kinetics, kinematics, and clinical measures of motor impairment, and was sensitive to walking ability according to the Gross Motor Functional Classification Scale (GMFCS). Overall, this methodology may have the potential to provide additional insight into the outcome of a clinical intervention that was not available previously, and may find use as a predictive tool that can be utilized for clinical decision making.
Lauer
Richard T
RT
Shriner's Hospitals for Children, Philadelphia, PA 19140, USA. rlauer@shrinenet.org
Stackhouse
Carrie A
CA
Shewokis
Patricia A
PA
Smith
Brian T
BT
Tucker
Carole A
CA
McCarthy
James
J
D000293:Adolescent; D000328:Adult; D001696:Biomechanical Phenomena; D002547:Cerebral Palsy / Q000503:physiopathology*; D002648:Child; D004576:Electromyography / Q000379:methods*; D005684:Gait / Q000502:physiology*; D006801:Humans; D025341:Principal Component Analysis; D012189:Retrospective Studies; D012815:Signal Processing, Computer-Assisted