Brain Machine Interface for Controlling Neuroprosthesis for Reaching and Grasping

神经假体是一种使用突发低能量电脉冲来产生肌肉收缩的设备。如果脉搏被正确地排序，它们可以在瘫痪的个体中产生诸如伸手、抓握和行走等动作。自2001年以来，我们的团队投入了大量的智力资本来开发用于伸展和抓取的神经假体。我们的技术与其他类似系统的不同之处在于，我们的神经假体不是用作永久性矫形器，患者需要随时使用才能接触和抓住。取而代之的是，我们使用神经假体作为一种短期的治疗干预，帮助中风和脊髓损伤患者对他们的中枢神经系统进行重新编程，并重新学习如何自己接触和抓住物体。我们将这种使用神经假体的新方法称为功能性电刺激疗法(FEST)。在FEST之后，在移除神经假体后，患者能够在没有设备帮助的情况下自行伸手和抓住。*脑机接口(BMI)是使用从大脑记录的电信号来控制计算机和机械臂等外部设备的系统。由于它们不需要任何运动(即肌肉收缩)来实现系统控制，BMI系统具有巨大的潜力来帮助严重残疾的人，如严重中风和脊髓损伤的人，执行他们无法独立执行的任务。2015年，我们的团队发现，如果FEST由BMI系统控制，BMI系统由与手打开和关闭相关的大脑信号触发，与传统的FEST训练相比，这种疗法会在大脑中产生更强、更有益的神经可塑性变化。*因此，该研究计划的目标是开发适合与FEST集成的各种BMI技术，并创造第一个临床可行的BMI+FEST干预。为了用体重指数系统控制FEST，体重指数必须能够确定：(I)患者打算进行什么伸展和抓握动作(S)；(Ii)患者希望执行这些任务的速度；以及(Iii)在任务执行过程中手臂的起始和结束位置。理想情况下，这应该是一个基于脑电(EEG)的非侵入性BMI系统。这项研究计划的具体目标是：任务1：开发一个能够使用脑电记录来检测手部姿势(如握手和横向握手)的BMI系统。任务2：开发一种BMI系统，能够使用脑电记录在3D空间中检测手的速度和位置。任务3：开发一个独立的硬件和软件平台，包括任务1和任务2中的BMI系统。任务4：探索使用微电极记录和单个神经元的可操作调节作为产生控制信号的手段，用于控制FEST。**

Neuroprostheses are devices that use bursts of low energy electrical pulses to generate muscle contractions. If the pulses are properly sequenced they can generate movements such as reaching, grasping and walking in individuals who are paralyzed. Since 2001, our team invested considerable amounts of intellectual capital to develop neuroprostheses for reaching and grasping. What differentiates our technology from other similar systems is that our neuroprostheses are not used as permanent orthoses patients need to use at all times to reach and grasp. Instead, we use neuroprosthesis as a short-term therapeutic intervention that helps stroke and spinal cord injury patients “reprogram” their central nervous system, and relearn how to reach and grasp objects on their own. We call this new way of using neuroprstheses the Functional Electrical Stimulation Therapy (FEST). Following FEST and after the neuroprosthesis is removed, the patients are able to reach and grasp on their own without help from the device.***Brain Machine Interfaces (BMIs) are systems that use electrical signals recorded from the brain to control external devices such as computers and robotic arms. Given that they do not require any movement (i.e. muscle contraction) to enable the system control, the BMI systems hold enormous potential to assist profoundly disabled individuals such as those with severe stroke and spinal cord injury, to perform tasks they are unable to carry out independently. In 2015 our team discovered that if the FEST is controlled by a BMI system, which is triggered by brain signals associated with hand opening and closing, that such therapy generates stronger and more beneficial neuroplastic changes in the brain as compared to conventional FEST training alone.***Therefore, the objective of this research program is to develop a variety of BMI technologies suitable for integration with FEST and to create first clinically viable BMI+FEST intervention. In order to control FEST with a BMI system, the BMI has to be able to determine: (i) what reaching and grasping movement(s) the patient intends to perform; (ii) the speed with which the patient would like these tasks to be performed; and (iii) initial and end positions of the arm during task execution. Ideally, this should be a non-invasive, electroencephalogram (EEG) -based BMI system. The specific objectives of this research program are: Task-1: Develop a BMI system able to detect the hand posture (e.g. pinch and lateral grasps) using EEG recordings. Task-2: Develop a BMI system able to detect the velocity and position of the hand in 3D space using EEG recordings. Task-3: Develop a self-contained hardware and software platform that incorporates BMI systems from Tasks 1 and 2. Task-4: Explore use of microelectrode recording and operant conditioning of single neurons as a means to generate control signals to be used to control FEST.**