IEEE Rev Biomed Eng. 2016;9:4-14. doi: 10.1109/RBME.2016.2552201. Epub 2016 Apr 8.
Since the late 1990s, there has been a burst of research on robotic devices for poststroke rehabilitation. Robot-mediated therapy produced improvements on recovery of motor capacity; however, so far, the use of robots has not shown qualitative benefit over classical therapist-led training sessions, performed on the same quantity of movements. Multidegree-of-freedom robots, like the modern upper-limb exoskeletons, enable a distributed interaction on the whole assisted limb and can exploit a large amount of sensory feedback data, potentially providing new capabilities within standard rehabilitation sessions. Surprisingly, most publications in the field of exoskeletons focused only on mechatronic design of the devices, while little details were given to the control aspects. On the contrary, we believe a paramount aspect for robots potentiality lies on the control side. Therefore, the aim of this review is to provide a taxonomy of currently available control strategies for exoskeletons for neurorehabilitation, in order to formulate appropriate questions toward the development of innovative and improved control strategies.
自 20 世纪 90 年代末以来,针对脑卒中后康复的机器人设备的研究呈爆发式增长。机器人介导的治疗在运动能力的恢复方面产生了改善;然而,到目前为止,机器人的使用并没有显示出比传统的、由治疗师主导的、在相同运动次数上进行的训练有质的好处。多自由度机器人,如现代上肢外骨骼,可以在整个辅助肢体上进行分布式交互,并可以利用大量的感觉反馈数据,在标准康复治疗中提供新的功能。令人惊讶的是,该领域的大多数外骨骼出版物仅关注于设备的机电设计,而很少涉及控制方面的细节。相反,我们认为机器人潜力的一个至关重要的方面在于控制方面。因此,本综述的目的是为神经康复用外骨骼提供当前可用的控制策略分类,以便为开发创新和改进的控制策略提出适当的问题。
IEEE Rev Biomed Eng. 2016-4-8
J Neuroeng Rehabil. 2017-6-12
Crit Rev Biomed Eng. 2016
IEEE Trans Neural Syst Rehabil Eng. 2017-2
J Neuroeng Rehabil. 2018-6-5
Proc Inst Mech Eng H. 2021-12
Phys Med Rehabil Clin N Am. 2019-5
J Healthc Eng. 2018-4-1
Sensors (Basel). 2025-7-17
J Neuroeng Rehabil. 2025-7-4
IEEE Trans Neural Syst Rehabil Eng. 2025
Wearable Technol. 2021-11-21
Bioengineering (Basel). 2023-11-17