Functional electrical stimulation mediated by iterative learning control and 3D robotics reduces motor impairment in chronic stroke.
Functional electrical stimulation mediated by iterative learning control and 3D robotics reduces motor impairment in chronic stroke.
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DOI：
10.1186/1743-0003-9-32
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发表时间：
2012-06-07
影响因子：
5.1
通讯作者：
Rogers E
中科院分区：
文献类型：
--
作者：
Meadmore KL;Hughes AM;Freeman CT;Cai Z;Tong D;Burridge JH;Rogers E
采用电刺激（ES）和机器人技术的新型中风康复技术在减少上肢损伤方面是有效的。当ES用于支持患者的自愿努力时，它是最有效的；然而，目前的系统无法充分利用这种联系。本研究建立在先前使用先进的ES控制器的工作基础上，旨在研究通过迭代学习刺激辅助（SAIL）的可行性，SAIL是一种利用机器人支持、ES和自愿努力的新型上肢中风康复系统。5名上肢功能受损的偏瘫、慢性中风参与者参加了18.1小时的干预。参与者完成了虚拟现实跟踪任务，他们移动受损的手臂，沿着指定的轨迹跟随缓慢移动的球体。为了做到这一点，参与者的手臂由机器人支撑。通过先进迭代学习控制（ILC）算法介导的ES应用于肱三头肌和前三角肌。每个动作重复6次，ILC调整每次试验施加的刺激量，以提高准确性和最大限度地发挥自主努力。参与者在基线和干预后完成临床评估（Fugl-Meyer，行动研究臂测试），并在每个干预阶段开始和结束时完成无辅助跟踪任务。数据分析采用t检验和线性回归。从基线到干预后，Fugl-Meyer评分提高，辅助和非辅助跟踪性能提高，辅助跟踪所需的ES量减少。演示了使用ILC算法最小化ES支持的概念。在减少中风后上肢损伤方面，积极的结果是有希望的，然而，需要更大规模的研究来证实这一点。
Novel stroke rehabilitation techniques that employ electrical stimulation (ES) and robotic technologies are effective in reducing upper limb impairments. ES is most effective when it is applied to support the patients’ voluntary effort; however, current systems fail to fully exploit this connection. This study builds on previous work using advanced ES controllers, and aims to investigate the feasibility of Stimulation Assistance through Iterative Learning (SAIL), a novel upper limb stroke rehabilitation system which utilises robotic support, ES, and voluntary effort. Five hemiparetic, chronic stroke participants with impaired upper limb function attended 18, 1 hour intervention sessions. Participants completed virtual reality tracking tasks whereby they moved their impaired arm to follow a slowly moving sphere along a specified trajectory. To do this, the participants’ arm was supported by a robot. ES, mediated by advanced iterative learning control (ILC) algorithms, was applied to the triceps and anterior deltoid muscles. Each movement was repeated 6 times and ILC adjusted the amount of stimulation applied on each trial to improve accuracy and maximise voluntary effort. Participants completed clinical assessments (Fugl-Meyer, Action Research Arm Test) at baseline and post-intervention, as well as unassisted tracking tasks at the beginning and end of each intervention session. Data were analysed using t-tests and linear regression. From baseline to post-intervention, Fugl-Meyer scores improved, assisted and unassisted tracking performance improved, and the amount of ES required to assist tracking reduced. The concept of minimising support from ES using ILC algorithms was demonstrated. The positive results are promising with respect to reducing upper limb impairments following stroke, however, a larger study is required to confirm this.
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影响因子：
105.7
作者：
MATTHEWS, JNS;ALTMAN, DG;ROYSTON, P
通讯作者：
ROYSTON, P
影响因子：
2.2
作者：
Kwakkel, Gert
通讯作者：
Kwakkel, Gert
DOI：
10.1097/00004356-198112000-00001
发表时间：
1981-01-01
影响因子：
1.7
作者：
LYLE, RC
通讯作者：
LYLE, RC
DOI：
10.1109/tnsre.2008.2010480
发表时间：
2009-02
期刊：
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
影响因子：
--
作者：
Hincapie JG;Kirsch RF
通讯作者：
Kirsch RF
影响因子：
8.3
作者：
Nichols-Larsen, DS;Clark, PC;Blanton, S
通讯作者：
Blanton, S