利用大鼠运动皮层的神经信号估计运动速度和方向变化以控制车辆。
Estimation of locomotion speed and directions changes to control a vehicle using neural signals from the motor cortex of rat.
作者信息
Fukayama Osamu, Taniguchi Noriyuki, Suzuki Takafumi, Mabuchi Kunihiko
机构信息
Graduate School of Information Science and Technology, University of Tokyo, Japan.
出版信息
Conf Proc IEEE Eng Med Biol Soc. 2006;2006:1138-41. doi: 10.1109/IEMBS.2006.260297.
We have developed a brain-machine interface (BMI) in the form of a small vehicle, which we call the RatCar. In this system, we implanted wire electrodes in the motor cortices of rat's brain to continuously record neural signals. We applied a linear model to estimate the locomotion state (e.g., speed and directions) of a rat using a weighted summation model for the neural firing rates. With this information, we then determined the approximate movement of a rat. Although the estimation is still imprecise, results suggest that our model is able to control the system to some degree. In this paper, we give an overview of our system and describe the methods used, which include continuous neural recording, spike detection and a discrimination algorithm, and a locomotion estimation model minimizes the square error of the locomotion speed and changes in direction.
我们开发了一种小型车辆形式的脑机接口（BMI），我们称之为“大鼠车”。在这个系统中，我们将线电极植入大鼠大脑的运动皮层，以持续记录神经信号。我们应用线性模型，通过对神经放电率使用加权求和模型来估计大鼠的运动状态（如速度和方向）。利用这些信息，我们随后确定大鼠的大致运动情况。尽管估计仍不精确，但结果表明我们的模型能够在一定程度上控制系统。在本文中，我们概述了我们的系统，并描述了所使用的方法，包括连续神经记录、尖峰检测和一种判别算法，以及一个使运动速度和方向变化的平方误差最小化的运动估计模型。
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