Putrino David, Wong Yan T, Vigeral Mariana, Pesaran Bijan
Center for Neural Science, New York University, USA.
Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:4567-70. doi: 10.1109/EMBC.2012.6346983.
As the field of neural prosthetics advances, Brain Machine Interface (BMI) design requires the development of virtual prostheses that allow decoding algorithms to be tested for efficacy in a time- and cost-efficient manner. Using an x-ray and MRI-guided skeletal reconstruction, and a graphic artist's rendering of an anatomically correct macaque upper limb, we created a virtual avatar capable of independent movement across 27 degrees-of-freedom (DOF). Using a custom software interface, we animated the avatar's movements in real-time using kinematic data acquired from awake, behaving macaque subjects using a 16 camera motion capture system. Using this system, we demonstrate real-time, closed-loop control of up to 27 DOFs in a virtual prosthetic device. Thus, we describe a practical method of testing the efficacy of high-complexity BMI decoding algorithms without the expense of fabricating a physical prosthetic.
随着神经假体领域的发展，脑机接口（BMI）设计需要开发虚拟假体，以便能够以高效省时且经济的方式测试解码算法的有效性。通过X射线和MRI引导的骨骼重建，以及图形艺术家对解剖学上正确的猕猴上肢的渲染，我们创建了一个能够在27个自由度（DOF）上独立运动的虚拟化身。使用定制的软件界面，我们利用从清醒、行为中的猕猴受试者通过16相机运动捕捉系统获取的运动学数据实时为化身的动作制作动画。利用该系统，我们展示了在虚拟假体装置中对多达27个自由度的实时闭环控制。因此，我们描述了一种测试高复杂性BMI解码算法有效性的实用方法，而无需花费制造物理假体的成本。
