Evaluation of a method to scale muscle strength for gait simulations of children with cerebral palsy

Abstract

Cerebral palsy (CP) is a neurological disorder that results in life-long mobility impairments. Musculoskeletal models used to investigate mobility deficits for children with CP often lack subject-specific characteristics such as altered muscle strength, despite a high prevalence of muscle weakness in this population. We hypothesized that incorporating subject-specific strength scaling within musculoskeletal models of children with CP would improve accuracy of muscle excitation predictions in walking simulations. Ten children (13.5 ± 3.3 years; GMFCS level II) with spastic CP participated in a gait analysis session where lower-limb kinematics, ground reaction forces, and bilateral electromyography (EMG) of five lower-limb muscles were collected. Isometric strength was measured for each child using handheld dynamometry. Three musculoskeletal models were generated for each child including a ‘Default’ model with the generic musculoskeletal model’s muscle strength, a ‘Uniform’ model with muscle strength scaled allometrically, and a ‘Custom’ model with muscle strength scaled based on handheld dynamometry strength measures. Muscle-driven gait simulations were generated using each model for each child. Simulation accuracy was evaluated by comparing predicted muscle excitations and measured EMG signals, both in the duration of muscle activity and the root-mean-square difference (RMSD) between signals. Improved agreement with EMG were found in both the ‘Custom’ and ‘Uniform’ models compared to the ‘Default’ model indicated by improvement in RMSD summed across all muscles, as well as RMSD and duration of activity for individual muscles. Incorporating strength scaling into musculoskeletal models can improve the accuracy of walking simulations for children with CP.