Department of Physical Medicine and Rehabilitation, Indiana University School of Medicine, 4141 Shore Drive, Indianapolis, IN, 46254, USA.
Rehabilitation Hospital of Indiana, Indianapolis, IN, USA.
J Neuroeng Rehabil. 2022 Jun 20;19(1):61. doi: 10.1186/s12984-022-01041-3.
The commentary by Dr. Labruyere on the article by Kuo et al. (J Neuroeng Rehabil. 2021; 18:174) posits that randomized trials evaluating the comparative efficacy of robotic devices for patients with neurological injury may not be needed. The primary argument is that researchers and clinicians do not know how to optimize training parameters to maximize the benefits of this therapy, and studies vary in how they deliver robotic-assisted training. While I concur with the suggestion that additional trials using robotic devices as therapeutic tools are not warranted, an alternative hypothesis is that future studies will yield similar equivocal results regardless of the training parameters used. Attempts are made to detail arguments supporting this premise, including the notion that the original rationale for providing robotic-assisted walking training, particularly with exoskeletal devices, was flawed and that the design of some of the more commonly used devices places inherent limitations on the ability to maximize neuromuscular demands during training. While these devices arrived nearly 20 years ago amid substantial enthusiasm, we have since learned valuable lessons from robotic-assisted and other rehabilitation studies on some of the critical parameters that influence neuromuscular and cardiovascular activity during locomotor training, and different strategies are now needed to optimize rehabilitation outcomes.
拉布鲁耶尔博士对郭等人的文章的评论（《神经工程与康复》，2021 年；18：174）认为，可能不需要评估机器人设备对神经损伤患者的比较疗效的随机试验。主要论点是，研究人员和临床医生不知道如何优化训练参数，以最大限度地发挥这种治疗的益处，而且研究在如何提供机器人辅助训练方面存在差异。虽然我同意使用机器人设备作为治疗工具的进一步试验没有必要的建议，但另一种假设是，无论使用何种训练参数，未来的研究都将产生类似的不确定结果。有人试图详细阐述支持这一前提的论点，包括这样一种观点，即提供机器人辅助行走训练（特别是使用外骨骼设备）的最初基本原理是有缺陷的，而且一些更常用设备的设计对在训练过程中最大限度地提高神经肌肉需求的能力存在固有限制。虽然这些设备在近 20 年前问世时引起了极大的热情，但从机器人辅助和其他康复研究中，我们已经学到了一些关于影响运动训练中神经肌肉和心血管活动的关键参数的宝贵经验，现在需要不同的策略来优化康复效果。
