Department of Physiotherapy and Rehabilitation, Institute of Health Sciences, Ankara Yıldırım Beyazıt University, Ankara, Turkey.
Department of Physical Therapy and Rehabilitation, Faculty of Health Sciences, Fırat University, Elazığ, Turkey.
Gait Posture. 2023 Jun;103:215-222. doi: 10.1016/j.gaitpost.2023.05.013. Epub 2023 May 18.
Stroke survivors often experience balance and gait problems, which can affect their quality of life and independence in daily living activities. Robot-assisted gait training, such as Lokomat with virtual reality, has been found to be effective in improving gait and balance. However, the specific effects of each virtual reality application on balance and spatiotemporal parameters of gait are not yet established. This study aims to investigate the effects of different virtual reality applications on these parameters.
What are the specific effects of each Lokomat augmented performance feedback application on balance and spatiotemporal parameters of gait in stroke survivors?
The study is a randomized controlled trial conducted with four groups: Control Group, Endurance Group, Attention and Motivation Group, and Activity Timing Group. All participants received six weeks of physiotherapy, and Lokomat groups had additional robot-assisted gait training with Lokomat for three days a week. The Endurance group used Lokomat with Faster, Attention and Motivation Group with Gabarello and Smile, and Activity Timing Group with Curve Pursuit, Treasures, and High Flyer applications. Various tests were used to assess walking and balance in the study (gait analysis, 6-minute walk test, 10-meter walk test, Berg Balance Scale, postural stability, and limits of stability).
The study involved 56 male stroke survivors (mean age: 60.02 ± 6.83 years, post-stroke time: 238.88 ± 40.88 days). All groups improved walking speed and distance significantly, but Endurance was better (p < 0.001). Balance improved significantly in all groups, but Attention and Motivation was superior in Berg Balance Scale, postural stability, and limits of stability (p < 0.001). The selection of virtual reality applications during robot-assisted gait training according to rehabilitation goals is important for successful rehabilitation, as these applications may have varying effects on balance and walking.
脑卒中幸存者常经历平衡和步态问题，这可能影响他们的生活质量和日常活动的独立性。机器人辅助步态训练，如 Lokomat 与虚拟现实，已被证实可有效改善步态和平衡。然而，每种虚拟现实应用对平衡和步态时空参数的具体影响尚未确定。本研究旨在探究不同虚拟现实应用对这些参数的影响。
每种 Lokomat 增强性能反馈应用对脑卒中幸存者平衡和步态时空参数的具体影响是什么？
本研究为随机对照试验，共分为四组：对照组、耐力组、注意力和动机组和活动计时组。所有参与者均接受六周的物理治疗，Lokomat 组在每周三天接受额外的机器人辅助步态训练。耐力组使用 Lokomat 与 Faster、注意力和动机组使用 Gabarello 和 Smile、活动计时组使用 Curve Pursuit、Treasures 和 High Flyer 应用。本研究使用多种测试来评估行走和平衡能力（步态分析、6 分钟步行测试、10 米步行测试、Berg 平衡量表、姿势稳定性和平衡极限）。
本研究共纳入 56 名男性脑卒中幸存者（平均年龄：60.02±6.83 岁，脑卒中后时间：238.88±40.88 天）。所有组的步行速度和距离均显著提高，但耐力组更佳（p<0.001）。所有组的平衡均显著改善，但注意力和动机组在 Berg 平衡量表、姿势稳定性和平衡极限方面表现更佳（p<0.001）。根据康复目标选择机器人辅助步态训练中的虚拟现实应用对于成功康复很重要，因为这些应用对平衡和行走的影响可能不同。
