A planar neuro-musculoskeletal arm model in post-stroke patients
Mathematical modeling of the neuro-musculoskeletal system in healthy subjects has been pursued extensively. In post-stroke patients, however, such models are very primitive. Besides improving our general understanding of how stroke affects the limb motions, they can be used to evaluate rehabilitation strategies by computer simulations before clinical evaluations. A planar neuro-musculoskeletal arm model for post-stroke patients is developed. The main idea is to use a set of new coefficients, Muscle Significance Factors (MSF), to incorporate the effects of stroke in the muscle control performance. The model uses the optimal control theory to mimic the performance of the CNS and a two-link skeletal model with six muscles for the biomechanical part. The model was developed and evaluated using experimental data from six post-stroke patients with Brunnstrom levels of 4–6. The results show that MSFs are relatively distinct and independent from the arm motion which is used to determine their values. Its variation is in the range of 0–2.58% and decreases in higher Brunnstrom levels. The mean error of the model in predicting the path of motion varies from 0.9% in level 6 to 5.58% in level 4 subjects which can be considered a promising level of accuracy. Using the proposed model and the MSF to customize the model for each individual stroke patient seems a promising approach. It shows a reasonable level of robustness, i.e., independence from the type of motions and correlated with the severity of stroke, and accuracy in predicting the shape of the motion path.
KeywordsOptimal control Musculoskeletal model CNS model of stroke patients Neuro-musculoskeletal arm model
This work was partially supported financially by Iran National Science Foundation, under Grant Number 92042014.
Compliance with ethical standards
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.
Informed consent was obtained from all individual participants included in the study.
- Charalambous CP (2014) Interrater reliability of a modified Ashworth scale of muscle spasticity. In: Classic papers in orthopaedics. SpringerGoogle Scholar
- Eberhart R, Kennedy J (1995) A new optimizer using particle swarm theory. In: Proceedings of the sixth international symposium on micro machine and human science, 1995. MHS’95. IEEE, pp 39–43Google Scholar
- Kirk DE (2004) Optimal Control Theory: An Introduction. Dover Publications, MineolaGoogle Scholar
- Todorov E, Li W (2003) Optimal control methods suitable for biomechanical systems. In: Engineering in medicine and biology society, 2003. Proceedings of the 25th annual international conference of the IEEE. IEEE, pp 1758–61Google Scholar