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首页> 外文期刊>Journal of Neuroscience Methods >Prediction of arm movement trajectories from ECoG-recordings in humans.
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Prediction of arm movement trajectories from ECoG-recordings in humans.

机译：根据人类的ECoG记录预测手臂的运动轨迹。

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Electrocorticographic (ECoG) signals have been shown to contain reliable information about the direction of arm movements and can be used for on-line cursor control. These findings indicate that the ECoG is a potential basis for a brain-machine interface (BMI) for application in paralyzed patients. However, previous approaches to ECoG-BMIs were either based on classification of different movement patterns or on a voluntary modulation of spectral features. For a continuous multi-dimensional BMI control, the prediction of complete movement trajectories, as it has already been shown for spike data and local field potentials (LFPs), would be a desirable addition for the ECoG, too. Here, we examined ECoG signals from six subjects with subdurally implanted ECoG-electrodes during continuous two-dimensional arm movements between random target positions. Our results show that continuous trajectories of 2D hand position can be approximately predicted from the ECoG recorded from hand/arm motor cortex. This indicates that ECoG signals, related to body movements, can directly be transferred to equivalent controls of an external effector for continuous BMI control.
机译：大脑皮层（ECoG）信号已显示包含有关手臂运动方向的可靠信息，并可用于在线光标控制。这些发现表明，ECoG是用于瘫痪患者的脑机接口（BMI）的潜在基础。但是，以前的ECoG-BMI方法要么基于不同运动模式的分类，要么基于频谱特征的自愿调制。对于连续的多维BMI控制，对于完整的运动轨迹的预测（如针对峰值数据和局部场电势（LFP）所显示的那样）对于ECoG也是一种理想的补充。在这里，我们检查了随机目标位置之间连续二维手臂运动期间硬膜下植入ECoG电极的六个受试者的ECoG信号。我们的结果表明，从手/手臂运动皮质记录的ECoG可以大致预测2D手位置的连续轨迹。这表明与身体运动有关的ECoG信号可以直接传输到外部执行器的等效控件，以进行连续BMI控制。

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