Androwis Ghaith J, Pilkar Rakesh, Ramanujam Arvind, Nolan Karen J
Human Performance and Engineering Research, Kessler Foundation, West Orange, NJ, United States.
Children's Specialized Hospital, Mountainside, NJ, United States.
Front Neurol. 2018 Aug 7;9:630. doi: 10.3389/fneur.2018.00630. eCollection 2018.
Robotic exoskeleton (RE) based gait training involves repetitive task-oriented movements and weight shifts to promote functional recovery. To effectively understand the neuromuscular alterations occurring due to hemiplegia as well as due to the utilization of RE in acute stroke, there is a need for electromyography (EMG) techniques that not only quantify the intensity of muscle activations but also quantify and compare activation timings in different gait training environments. To examine the applicability of a novel EMG analysis technique, Burst Duration Similarity Index (BDSI) during a single session of inpatient gait training in RE and during traditional overground gait training for individuals with acute stroke. Surface EMG was collected bilaterally with and without the RE device for five participants with acute stroke during the normalized gait cycle to measure lower limb muscle activations. EMG outcomes included integrated EMG (iEMG) calculated from the root-mean-square profiles, and a novel measure, BDSI derived from activation timing comparisons. EMG data demonstrated volitional although varied levels of muscle activations on the affected and unaffected limbs, during gait with and without the RE. During the stance phase mean iEMG of the soleus ( = 0.019) and rectus femoris (RF) ( = 0.017) on the affected side significantly decreased with RE, as compared to without the RE. The differences in mean BDSI scores on the affected side with RE were significantly higher than without RE for the vastus lateralis (VL) ( = 0.010) and RF ( = 0.019). A traditional amplitude analysis (iEMG) and a novel timing analysis (BDSI) techniques were presented to assess the neuromuscular adaptations resulting in lower extremities muscles during RE assisted hemiplegic gait post acute stroke. The RE gait training environment allowed participants with hemiplegia post acute stroke to preserve their volitional neuromuscular activations during gait iEMG and BDSI analyses showed that the neuromuscular changes occurring in the RE environment were characterized by correctly timed amplitude and temporal adaptations. As a result of these adaptations, VL and RF on the affected side closely matched the activation patterns of healthy gait. Preliminary EMG data suggests that the RE provides an effective gait training environment for in acute stroke rehabilitation.
基于机器人外骨骼(RE)的步态训练涉及重复性的任务导向运动和重心转移,以促进功能恢复。为了有效理解偏瘫以及在急性中风中使用RE所导致的神经肌肉改变,需要肌电图(EMG)技术,该技术不仅能量化肌肉激活的强度,还能在不同的步态训练环境中量化并比较激活时间。为了检验一种新型EMG分析技术——爆发持续时间相似性指数(BDSI)在急性中风患者住院期间单次RE步态训练以及传统地面步态训练中的适用性。在正常步态周期内,对五名急性中风患者在使用和不使用RE设备的情况下双侧采集表面肌电图,以测量下肢肌肉激活情况。EMG结果包括根据均方根曲线计算得出的积分肌电图(iEMG),以及一种从激活时间比较中得出的新指标BDSI。EMG数据显示,在有和没有RE的步态过程中,患侧和健侧肢体的肌肉激活水平虽有变化但都是自主的。在站立期,与不使用RE相比,使用RE时患侧比目鱼肌的平均iEMG( = 0.019)和股直肌(RF)( = 0.017)显著降低。对于外侧股四头肌(VL)( = 0.010)和RF( = 0.019),使用RE时患侧的平均BDSI分数差异显著高于不使用RE时。提出了一种传统的幅度分析(iEMG)和一种新的时间分析(BDSI)技术,以评估急性中风后RE辅助偏瘫步态期间下肢肌肉的神经肌肉适应性。RE步态训练环境使急性中风后偏瘫的参与者在步态iEMG和BDSI分析期间能够保持其自主神经肌肉激活。结果表明,在RE环境中发生的神经肌肉变化具有正确定时的幅度和时间适应性特征。由于这些适应性变化,患侧的VL和RF与健康步态的激活模式紧密匹配。初步的EMG数据表明,RE为急性中风康复提供了一个有效的步态训练环境。