专利快速检索-快速检索全球专利，免费商用专利数据库-IPRDB

1. 发明申请

US20040073414A1 Method and system for inferring hand motion from multi-cell recordings in the motor cortex using a kalman filter or a bayesian model 审中-公开
标题翻译：使用卡尔曼滤波器或贝叶斯模型从运动皮质中的多细胞记录推断手运动的方法和系统
公开(公告)号：US20040073414A1
公开(公告)日：2004-04-15
申请号：US10455509
申请日：2003-06-04
申请人： Brown University Research Foundation
发明人： Lucien J.E. Bienenstock , Michael J. Black , Wei Wu , Yun Gao
IPC分类号： G06F017/10
CPC分类号： G06F3/015
摘要： A method and system to decode neural activity in the motor cortex to infer at least the position and velocity of a subject's hand from neural spiking activity of some number of nerve cells. In one embodiment the method includes simultaneously recording electrical activity of the nerve cells in the primary motor cortex to obtain neural data; and modeling the encoding and decoding of the neural data using a Kalman filter, where a measurement model assumes a cell firing rate to be a stochastic linear function of at least the position and velocity of the hand, and where the measurement model is learned from training data in conjunction with a system model that encodes a manner in which the hand moves. In another embodiment the method includes using the neural data to generate training data of neural firing activity conditioned on hand kinematics; learning a non-parametric representation of the firing activity using a Bayesian model; inferring an a posterior probability distribution over hand motion, conditioned on the neural training data using Bayesian inference; defining a non-Gaussian likelihood term that is combined with a prior probability for the kinematics based on learned firing models of multiple nerve cells; and using a particle filtering method is to represent, update, and propagate the posterior distribution over time.
摘要翻译：一种解决运动皮层神经活动的方法和系统，至少推断受试者的手从一些神经细胞的神经刺激活动的位置和速度。在一个实施方案中，该方法包括同时记录神经细胞在主运动皮层中的电活动以获得神经数据; 并且使用卡尔曼滤波器对神经数据的编码和解码进行建模，其中测量模型假定小区发射速率至少是手的位置和速度的随机线性函数，并且其中从训练中学习测量模型数据结合编码手移动方式的系统模型。在另一个实施例中，该方法包括使用神经数据来产生以手运动学为条件的神经发射活动的训练数据; 使用贝叶斯模型学习射击活动的非参数表示; 推导使用贝叶斯推理的神经训练数据的手部运动后验概率分布; 基于多个神经细胞的学习的发射模型定义与运动学的先验概率相结合的非高斯似然项; 并且使用粒子滤波方法是表示，更新和传播随时间的后验分布。

IPRDB

热门服务

关于我们

友情链接

联系方式