Department of Health Sciences and Research, College of Health Professions, Medical University of South Carolina, 77 President Street, Charleston, SC, 29425, USA.
Biomechanics, Rehabilitation, and Integrative Neuroscience (BRaIN) Lab, Department of Physical Medicine and Rehabilitation, University of California Davis School of Medicine, Sacramento, CA, 95817, USA.
J Neuroeng Rehabil. 2019 Jan 31;16(1):21. doi: 10.1186/s12984-019-0487-y.
Stroke survivors often have lower extremity sensorimotor impairments, resulting in an inability to sufficiently recruit muscle activity at appropriate times in a gait cycle. Currently there is a lack of a standardized method that allows comparison of muscle activation in hemiparetic gait post-stroke to a normative profile.
We developed a new tool to quantify altered muscle activation patterns (AMAP). AMAP accounts for spatiotemporal asymmetries in stroke gait by evaluating the deviations of muscle activation specific to each gait sub-phase. It also recognizes the characteristic variability within the healthy population. The inter-individual variability of normal electromyography (EMG) patterns within some sub-phases of the gait cycle is larger compared to others, therefore AMAP penalizes more for deviations in a gait sub-phase with a constant profile (absolute active or inactive) vs variable profile. EMG data were collected during treadmill walking, from eight leg muscles of 34 stroke survivors at self-selected speeds and 20 healthy controls at four different speeds. Stroke survivors' AMAP scores, for timing and amplitude variations, were computed in comparison to healthy controls walking at speeds matched to the stroke survivors' self-selected speeds.
Altered EMG patterns in the stroke population quantified using AMAP agree with the previously reported EMG alterations in stroke gait that were identified using qualitative methods. We defined scores ranging between ±2.57 as "normal". Only 9% of healthy controls were outside "normal" window for timing and amplitude. Percentages of stroke subjects outside the "normal" window for each muscle were, Soleus = 79%; 73%, Medial Gastrocnemius = 62%; 79%, Tibialis Anterior = 62%; 59%, and Gluteus Medius = 48%; 51% for amplitude and timing component respectively, alterations were relatively smaller for the other four muscles. Paretic-propulsion was negatively correlated to AMAP scores for the timing component of Soleus. Stroke survivors' self-selected walking speed was negatively correlated with AMAP scores for amplitude and timing of Soleus but only amplitude of Medial gastrocnemius (p < 0.05).
Our results validate the ability of AMAP to identify alterations in the EMG patterns within the stroke population and its potential to be used to identify the gait phases that may require more attention when developing an optimal gait training paradigm.
ClinicalTrials.gov NCT00712179 , Registered July 3rd 2008.
脑卒中幸存者常存在下肢感觉运动功能障碍，导致在步态周期中无法适时充分募集肌肉活动。目前，缺乏一种标准化的方法来比较脑卒中后偏瘫步态中的肌肉激活情况与正常模式。
我们开发了一种新的工具来量化异常的肌肉激活模式（AMAP）。AMAP 通过评估每个步态亚相特有的肌肉激活偏差，考虑到脑卒中步态中的时空不对称性。它还可以识别健康人群中的特征变异性。与其他亚相相比，一些步态周期亚相中正常肌电图（EMG）模式的个体间变异性更大，因此，与具有恒定（绝对活动或不活动）和可变形态的步态亚相相比，AMAP 会对偏差进行更多的惩罚。在跑步机上行走时，从 34 名脑卒中幸存者的 8 条腿部肌肉和 20 名健康对照者的 4 条不同速度采集 EMG 数据。根据与脑卒中幸存者自选择速度相匹配的速度，计算脑卒中幸存者的 AMAP 评分，用于评估时程和幅度变化。
脑卒中患者群体中使用 AMAP 量化的异常 EMG 模式与之前使用定性方法在脑卒中步态中报告的 EMG 改变一致。我们定义了介于±2.57 之间的分数为“正常”。只有 9%的健康对照者的时程和幅度超出“正常”范围。对于每个肌肉，超出“正常”范围的脑卒中患者百分比分别为：比目鱼肌=79%；内侧腓肠肌=73%；胫骨前肌=62%；臀中肌=48%；时程和幅度分量分别为 59%。其他四个肌肉的改变相对较小。患侧推进力与比目鱼肌的时程 AMAP 评分呈负相关。脑卒中幸存者的自选择行走速度与比目鱼肌的幅度和时程 AMAP 评分呈负相关，但仅与内侧腓肠肌的幅度 AMAP 评分呈负相关（p<0.05）。
我们的结果验证了 AMAP 识别脑卒中患者群体中 EMG 模式改变的能力，以及其在确定需要在优化步态训练方案中给予更多关注的步态相方面的潜力。
ClinicalTrials.gov NCT00712179，2008 年 7 月 3 日注册。
