Ebihara Akira, Hirota Mitsuki, Kumakura Yasuhiro, Nagaoka Masanori
Department of Rehabilitation, Tsubasa-no-ie Hospital, Oyama, Tochigi, Japan.
Department of Rehabilitation Medicine, Dokkyo Medical University, Shimotsugagun, Tochigi, Japan.
Front Hum Neurosci. 2024 Jan 9;17:1287675. doi: 10.3389/fnhum.2023.1287675. eCollection 2023.
We conducted muscle synergy and gait analyses in a monoplegic patient whose gait function improved through training, to explore the possibility of using these parameters as indicators of training.
A 49-year-old male had monoplegia of the right lower limb caused by infarction of the left paracentral lobule. After 2 months of training, he was able to walk and returned to work.
Consecutive analyses were done after admission. Muscle synergy analysis: during walking, surface electromyograms of gluteus maximus, quadriceps femoris, adductor femoris, hamstrings, tibialis anterior, medial/lateral gastrocnemius, and soleus on both sides were recorded and processed for non-negative matrix factorization (NNMF) analysis. Gait analysis: markers were placed at foot, and walking movements were video recorded as changes in position of the markers.
Compared with three muscle synergies detected on the non-paretic side, two muscle synergies were extracted on the paretic side at admission, and the number increased to three and then four with progress in rehabilitation training. Changes in weighting and activity of the muscle synergies were greater on the non-paretic side than on the paretic side. With training, the knee joint flexor and the ankle dorsiflexor activities on the paretic side and the gluteus maximus activity on the non-paretic side increased during swing phase as shown by weight changes of muscle synergies, and gait analysis showed increased knee joint flexion and ankle joint dorsiflexion during swing phase in the paretic limb. On the non-paretic side, however, variability of muscle activity was observed, and three or four muscle synergies were extracted depending on the number of strides analyzed.
The number of muscle synergies is considered to contribute to motor control. Rehabilitation training improves gait by increasing the number of muscle synergies on the paretic side and changing the weights of the muscles constituting the muscle synergies. From the changes on the non-paretic side, we propose the existence of compensatory mechanisms also on the non-paretic side. In muscle synergy analysis, in addition to the filters, the number of strides used in each analysis set has to be examined. This report highlights the issues of NNMF as analytical methods in gait training for stroke patients.
我们对一名通过训练步态功能得到改善的单瘫患者进行了肌肉协同和步态分析，以探讨将这些参数用作训练指标的可能性。
一名49岁男性因左侧中央旁小叶梗死导致右下肢单瘫。经过2个月的训练，他能够行走并重返工作岗位。
入院后进行连续分析。肌肉协同分析：在步行过程中，记录双侧臀大肌、股四头肌、股内收肌、腘绳肌、胫骨前肌、腓肠肌内侧/外侧和比目鱼肌的表面肌电图，并进行非负矩阵分解（NNMF）分析。步态分析：在足部放置标记物，将步行运动作为标记物位置的变化进行视频记录。
与非瘫痪侧检测到的三种肌肉协同相比，入院时瘫痪侧提取到两种肌肉协同，随着康复训练的进展，数量增加到三种，然后是四种。非瘫痪侧肌肉协同的权重和活动变化大于瘫痪侧。通过训练，肌肉协同权重变化显示，摆动期瘫痪侧膝关节屈肌和踝关节背屈肌活动以及非瘫痪侧臀大肌活动增加，步态分析显示瘫痪侧肢体摆动期膝关节屈曲和踝关节背屈增加。然而，在非瘫痪侧观察到肌肉活动的变异性，根据分析的步数提取三种或四种肌肉协同。
肌肉协同的数量被认为有助于运动控制。康复训练通过增加瘫痪侧肌肉协同的数量和改变构成肌肉协同的肌肉权重来改善步态。从非瘫痪侧的变化来看，我们提出非瘫痪侧也存在代偿机制。在肌肉协同分析中，除了滤波器外，还必须检查每个分析集使用的步数。本报告强调了NNMF作为中风患者步态训练分析方法的问题。
