Analysis of the Relationship Between Muscle Tones and Abnormal Postures in a Computational Model.

Patients with Parkinson's disease (PD), a neurodegenerative disorder, exhibit a characteristic posture known as a forward flexed posture. Increased muscle tone is suggested as a possible cause of this abnormal posture. For further analysis, it is necessary to measure muscle tone, but the experimental measurement of muscle tone during standing is challenging. The aim of this study was to examine the hypothesis that "In patients with PD, abnormal postures are those with a small sway at increased muscle tones" using a computational model. The muscle tones of various magnitudes were estimated using the computational model and standing data of patients with PD. The postures with small sway at the estimated muscle tones were then calculated through an optimization method. The postures and sway calculated using the computational model were compared to those of patients with PD. The results showed that the differences in posture and sway between the simulation and experimental results were small at higher muscle tones compared to those considered plausible in healthy subjects by the simulations. This simulation result indicates that the reproduced sway at high muscle tones is similar to that of actual patients with PD and that the reproduced postures with small sway locally at high muscle tones in the simulations are similar to those of patients with PD. The result is consistent with the hypothesis, reinforcing the hypothesis.Clinical relevance- This study implies that improving the increased muscle tone in patients with PD may lead to an improved abnormal posture.

Citation

Yuichiro Omura, Hiroki Togo, Kohei Kaminishi, Tetsuya Hasegawa, Ryosuke Chiba, Arito Yozu, Kaoru Takakusaki, Mitsunari Abe, Yuji Takahashi, Takashi Hanakawa, Jun Ota. Analysis of the Relationship Between Muscle Tones and Abnormal Postures in a Computational Model. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. 2023 Jul;2023:1-4

Mesh Tags

PMID: 38083325

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