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Analyzing the Kinematic Synergies of Cerebral Palsy Patients in Comparison with Healthy Individuals Based on Identical Activation Patterns

Salehizadeh, Mohammad Saleh | 2024

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 57759 (08)
  4. University: Sharif University of Technology
  5. Department: Mechanical Engineering
  6. Advisor(s): Farahmand, Farzam
  7. Abstract:
  8. One of the common motor disorders among children is cerebral palsy. On average, 1 to 4 out of every 1000 children born are affected by this disease. Defects in the central nervous system, along with musculoskeletal system disorders, are noticeable in cerebral palsy. In recent years, various methods have been proposed for motor control analysis. One of these methods is the synergy hypothesis, which can be used to explain the performance of the central nervous system in controlling and moving body parts. However, in previous studies, the kinematic synergies of healthy and cerebral palsy groups have often been extracted separately without considering their interrelation. Typically, four or five synergies are used to describe the gait of healthy humans, and one to four synergies are used for cerebral palsy patients. Due to the difference in the number of synergies obtained in the two groups under study, it becomes impossible to analyze and compare the results on a one-to-one basis. In this study, by considering the number of synergies and activation patterns of each one as equal, it was possible to compare the weight structures in each synergy of cerebral palsy patients with healthy individuals on a one-to-one basis. For this purpose, the non-negative matrix factorization algorithm was used to extract the synergies of the healthy group, and the non-negative least squares algorithm was used to impose the activators of the healthy group on the patients. Then, to examine the differences in the motor complexities of patients compared to healthy individuals, the probability of merging their motor characteristics was studied using the inner product of the weight modules in each motor characteristic. Additionally, based on which modules were found to be similar, a new grouping for patients was proposed. For this purpose, the similarity graph of the weight structures and its corresponding matrix were defined to provide a suitable algorithm for identifying acceptable groupings, regardless of the number of motor characteristics. Finally, to study patients who have the ability to move similarly to healthy individuals and whose gait abnormalities are due to different neural signals, a method was developed to impose the weight structures of the healthy group on the patients. According to this method, the activators of the healthy group were first fitted by three terms of the Fourier series, and a parametric equation with eight variable coefficients was obtained. By determining the coefficients of this equation using the sequential quadratic programming algorithm, the activators of the patients were obtained. However, considering that cerebral palsy usually occurs before birth or shortly after birth, this assumption is not valid for cerebral palsy patients, and its main application can be envisioned for stroke patients. One of the findings of this research is that if the EEG data of patients is recorded simultaneously with their kinematic data, after decoding the EEG signals, they can be used as activation patterns. It was also shown that among the overall group of CP patients, 23% are single-synergy, 26% double-synergy, 35% triple-synergy, and 16% quadruple-synergy. If we consider Rodda’s CP classification, in the apparent category, the single-synergy, double-synergy, triple-synergy, and quadruple-synergy groups cover 6%, 39%, 39%, and 17% of the members, respectively. The same results for the crouch category are 60%, 13%, 23%, and 3%, for the jump category 16%, 32%, 32%, and 20%, and for the true category 9%, 24%, 47%, and 21%
  9. Keywords:
  10. Gait Analysis ; Sequential Quadratic Programming (SQP) ; Non-Negative Least Squares (NNLS) ; Mergeability ; Non-Negative Matrix Factorization ; Imposing Activation Patterns ; Cerebral Palsy

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