As computer science progresses, neuromusculoskeletal models are increasingly applied in clinical settings, particularly when studying abnormal characteristics in patients with cerebral palsy. Digital neuromusculoskeletal models enable researchers and clinicians to gain a deeper understanding of movement mechanisms, providing additional insights for diagnosis and treatment. While biomechanical simulation platforms like OpenSim offer standardized neuromusculoskeletal models for simulation, relying on generic healthy models to simulate movements in cerebral palsy patients can lead to inaccuracies. Therefore, personalized muscle-tendon parameters are essential for cerebral palsy patient models. In this study, we collected ultrasound video data of the semitendinosus muscle from two patients with cerebral palsy during the passive knee extension process. We proposed a muscle-tendon parameter personalization method and developed the individualized OpenSim models for the patients using this data. We validated the personalized models' output fiber length and pennation angle through a series of hip flexion movement tests. The experimental results demonstrate that using the personalized muscle model for cerebral palsy patients produces muscle fiber length and pennation angle more closely aligned with ultrasound-measured values. After personalization, the RMSE between model output and ultrasound measurement of muscle fiber length and pennation angle decreased by 96.80% and 61.80%, respectively, averaged across both subjects. This study introduces a method for determining muscle-tendon parameters in cerebral palsy patients' digital neuromusculoskeletal models, providing researchers and clinicians with more precise biomechanical information. These insights can better inform the treatment of cerebral palsy patients, ultimately enhancing therapeutic outcomes.