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Brain controlled robotic exoskeleton for neurorehabilitation

机译:用于神经康复的脑控制机器人外骨骼

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Robots have been used for decades to enhance productivity, reliability and accuracy for repetitive tasks. More recently robot capabilities have been exploited in medical rehabilitation applications for this same reason. While robots can provide consistent physical therapy there is limited evidence that robot assisted physical therapy has any improved outcomes over human administered therapy. Patient participation is the most important factor for rehabilitating the neural system after injury or stroke and so this research develops a new method for re-connecting the brain to the limbs of a patient. Steady state visual evoked potential (SSVEP) signals are read and decoded to extract the user's intent, and then used to control a robot exoskeleton to move the patient's limbs for therapy. This artificial reconnection of the brain to the limbs allows therapy in a natural way and provides positive reinforcement for learning and so it is believed it will result in improved outcomes. Two different training protocols are proposed and tested to allow real-time brain control of a lower limb rehabilitation device. Results with healthy patients are extremely good with accuracy to within a knee angle of 1° at 100% reliability after simple training. This gives much promise to future development of brain controlled rehabilitation devices.
机译:机器人已经使用了数十年,以提高重复任务的生产率,可靠性和准确性。出于同样的原因,近来机器人功能已经在医疗康复应用中得到了利用。虽然机器人可以提供一致的物理治疗,但是有限的证据表明,机器人辅助的物理治疗比人类进行的治疗具有任何改善的结果。病人的参与是在受伤或中风后恢复神经系统的最重要因素,因此这项研究开发了一种新的方法,可以将大脑重新连接到病人的四肢。读取并解码稳态视觉诱发电位(SSVEP)信号以提取用户的意图,然后将其用于控制​​机器人外骨骼以移动患者的四肢进行治疗。大脑与四肢的这种人工重新连接可以自然方式进行治疗,并为学习提供积极的支持,因此可以相信它将导致改善的结局。提出并测试了两种不同的训练方案,以允许对下肢康复设备进行实时大脑控制。简单训练后,健康患者的结果非常好,准确度可达到1°的膝关节角度,并且100%的可靠性。这为大脑控制的康复设备的未来发展提供了很大的希望。

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