Interpretation of surface EMGs in children with cerebral palsy: An initial study using a fuzzy expert system
Autor: | Catherine Disselhorst-Klug, Sybele Williams, Günther Rau, Bernhard Schmidt-Rohlfing, Hans Josef Erli, Ferdinand Bergamo, Fritz Niethard |
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Rok vydání: | 2006 |
Předmět: |
Male
medicine.medical_specialty Computer science Expert Systems Kinematics computer.software_genre Fuzzy logic Pattern Recognition Automated Cerebral palsy Gait (human) Fuzzy Logic medicine Humans Orthopedics and Sports Medicine Child Muscle Skeletal Gait Disorders Neurologic Interpretation (logic) Electromyography Cerebral Palsy Reproducibility of Results medicine.disease Expert system medicine.anatomical_structure Child Preschool Gait analysis Physical therapy Feasibility Studies Female Neural Networks Computer Ankle computer |
Zdroj: | Journal of Orthopaedic Research. 24:438-447 |
ISSN: | 1554-527X 0736-0266 |
Popis: | Surface EMG detected simultaneously at different muscles has become an important tool for analysing the gait of children with cerebral palsy (CP), as it offers essential information about muscular coordination. However, the interpretation of surface EMG is a difficult task that assumes extensive knowledge and experience. As such, this noninvasive procedure is not frequently used in the general clinical routine. An Artificial Intelligence (AI) system for interpreting surface EMG signals and the resulting muscular coordination patterns could overcome these limitations. To support such interpretation, an expert system based on fuzzy inference methodology was developed. The knowledge-base of the system implemented 15 rules, from which the fuzzy inference methodology performs a prediction of the effectiveness of the muscular coordination during gait. Our aim was to assess the feasibility and value of such an expert system in clinical applications. Surface EMG signals were recorded from the tibialis anterior, soleus muscle, and gastrocnemius muscles of children with CP to assess muscular coordination patterns of ankle movement during gait. Nineteen children underwent 114 surface EMG measurements. Simultaneously, the gait cycles of each patient were determined using foot switches and videotapes. From the EMG signals, the effectiveness of the ankle movement was predicted by the expert system, and predictions were classified using a three-point ordinal scale. In 91 cases (80%), the clinical findings matched the predictions of the expert system. In 23 cases (20%) the predictions of the expert system differed from the clinical findings with 12 cases revealing worse and 11 cases revealing better results in comparison to the clinical findings. As this study is a first attempt to verify the feasibility and correctness of this expert system, the results are promising. Further study is required to assess the correlation with the kinematic data and to include the whole leg. © 2006 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 24:438–447, 2006 |
Databáze: | OpenAIRE |
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