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Classification of Children with Cerebral Palsy Using Gait Analysis Data

Darbandi, Hamed | 2017

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 50516 (08)
  4. University: Sharif University of Technology
  5. Department: Mechanical Engineering
  6. Advisor(s): Farahmand, Farzam; Behzadipour, Saeed
  7. Abstract:
  8. Cerebral palsy is a disorder and a condition that occurs before, during or after birth. According to reports, in developing countries, out of every 1,000 births, 3.5 cases develop cerebral palsy. One of the consequences of cerebral palsy is unusual walking due to nerve disorders, including severe spasm of the lower muscles of the trunk. Drugs, therapies, and orthopedic surgeries are used to help patients with cerebral palsy. Improper orthopedic surgeries have severe effects on the patient's function. You can partially solve these problems by using the gateway category. The common patterns of cerebral palsy gait help decide the treatment method. In recent years, the use of gait analysis has been considered to diagnose anomalies and design appropriate treatment in children with cerebral palsy, but there is still no agreement on how to interpret the results of the gait analysis. The aim of this study is to determine the qualitative classification of children with cerebral palsy using a fuzzy system so that they can be placed with the specific parameters in the gate in the appropriate category and based on the appropriate treatment plan. During this study, eighty-eight children with cerebral palsy who are able to walk will have gait analysis and kinematic, dynamic, and muscular activity data. Then, according to the classified data, the effective parameters in the gait will be identified. By defining the parameters and defining a fuzzy system based on it, the categorization of patients will be quantitatively performed. By categorizing patients, the decision on the patient's treatment method will be determined more precisely. A fuzzy system that categorizes patients using effective parameters is able to accommodate each patient in a specific category using only certain parameters and not all raw data analysis. The enclosed area between the angular pattern of the patient's joints and the normal is an effective criterion, and in 9 charts of 12 charts this criterion can be observed. Also, the speed of movement of the ankle and the knee during to-be is another determining factor
  9. Keywords:
  10. Gait Analysis ; Classification ; Fuzzy Systems ; Parameters ; Quantification ; Cerebral Palsy ; Golden Standard

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