Guo Zhao, Ye Jing, Zhang Shisheng, Xu Lanshuai, Chen Gong, Guan Xiao, Li Yongqiang, Zhang Zhimian
School of Power and Mechanical Engineering, Wuhan University, Wuhan, China.
Shenzhen Milebot Robotics Co., Ltd., Shenzhen, China.
Front Neurorobot. 2022 Mar 8;15:817446. doi: 10.3389/fnbot.2021.817446. eCollection 2021.
Lower-limb exoskeleton robots are being widely used in gait rehabilitation training for patients with stroke. However, most of the current rehabilitation robots are guided by predestined gait trajectories, which are often different from the actual gait trajectories of specific patients. One solution is to train patients using individualized gait trajectories generated from the physical parameters of patients. Hence, we aimed to explore the effect of individual gaits on energy consumption situations during gait rehabilitation training for hemiplegic patients with lower-limb exoskeleton robots.
A total of 9 unilateral-hemiplegic patients were recruited for a 2-day experiment. On the first day of the experiment, the 9 patients were guided by a lower-limb exoskeleton robot, walking on flat ground for 15 min in general gait trajectory, which was gained by clinical gait analysis (CGA) method. On the other day, the same 9 patients wore the identical robot and walked on the same flat ground for 15 min in an individualized gait trajectory. The main physiological parameters including heart rate (HR) and peripheral capillary oxygen saturation (SpO2) were acquired cardio tachometer and oximeter before and after the walking training. The energy consumption situation was indicated by the variation of the value of HR and SpO2 after walking training compared to before.
Between-group comparison showed that the individualized gait trajectory training resulted in an increase in HR levels and a decrease in SpO2 levels compared to the general gait trajectory training. The resulting difference had a statistical significance of < 0.05.
Using individualized gait guidance in rehabilitation walking training can significantly improve energy efficiency for hemiplegic patients with stroke.
下肢外骨骼机器人正广泛应用于中风患者的步态康复训练。然而，当前大多数康复机器人是按照预定的步态轨迹进行引导的，这些轨迹往往与特定患者的实际步态轨迹不同。一种解决方案是使用根据患者身体参数生成的个性化步态轨迹来训练患者。因此，我们旨在探讨使用下肢外骨骼机器人对偏瘫患者进行步态康复训练时，个性化步态对能量消耗情况的影响。
共招募了9名单侧偏瘫患者进行为期2天的实验。在实验的第一天，这9名患者由下肢外骨骼机器人引导，在平坦地面上按照通过临床步态分析（CGA）方法获得的一般步态轨迹行走15分钟。在另一天，同样的9名患者穿戴相同的机器人，在相同的平坦地面上按照个性化步态轨迹行走15分钟。在行走训练前后，使用心率计和血氧饱和度仪获取包括心率（HR）和外周毛细血管血氧饱和度（SpO2）在内的主要生理参数。能量消耗情况通过行走训练后与训练前HR和SpO2值的变化来表示。
组间比较显示，与一般步态轨迹训练相比，个性化步态轨迹训练导致HR水平升高，SpO2水平降低。由此产生的差异具有统计学意义（P<0.05）。
在康复行走训练中使用个性化步态引导可以显著提高中风偏瘫患者的能量效率。
