Prediction of hand trajectory from electrocorticography signals in primary motor cortex.
Prediction of hand trajectory from electrocorticography signals in primary motor cortex.
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DOI：
10.1371/journal.pone.0083534
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发表时间：
2013
期刊：
影响因子：
3.7
通讯作者：
Koike Y
中科院分区：
文献类型：
--
作者：
Chen C;Shin D;Watanabe H;Nakanishi Y;Kambara H;Yoshimura N;Nambu A;Isa T;Nishimura Y;Koike Y
由于其作为脑机接口的控制模式的潜力，皮层电图（ECoG）近年来受到了广泛的关注。利用ECoG的研究已经在手臂运动和自然抓握类型的分类、手臂运动轨迹的二维和三维回归、肌肉活动时间序列的估计等方面取得了成功，但在实现高性能的基于ECoG的神经假肢之前还有大量的工作要做。在这项研究中，我们提出了一种算法，解码的手轨迹从15和32通道ECoG信号记录的初级运动皮层（M1）在两个灵长类动物。为了确定最有效的预测区域，我们应用了两种电极选择方法，一种基于相对于中央沟（CS）的位置，另一种基于电极的个体预测性能。两种猴对手轨迹解码的最佳决定系数分别为0.4815±0.0167和0.7780±0.0164。来自个体ECoG电极的性能结果表明，具有较高性能的那些电极集中在侧部区域和靠近CS的区域。根据所提出的方法的不同数量的电极的预测结果也显示和讨论。这些结果还表明，可以通过一组有效的ECoG信号而不是整个ECoG阵列来实现上级解码性能。
Due to their potential as a control modality in brain-machine interfaces, electrocorticography (ECoG) has received much focus in recent years. Studies using ECoG have come out with success in such endeavors as classification of arm movements and natural grasp types, regression of arm trajectories in two and three dimensions, estimation of muscle activity time series and so on. However, there still remains considerable work to be done before a high performance ECoG-based neural prosthetic can be realized. In this study, we proposed an algorithm to decode hand trajectory from 15 and 32 channel ECoG signals recorded from primary motor cortex (M1) in two primates. To determine the most effective areas for prediction, we applied two electrode selection methods, one based on position relative to the central sulcus (CS) and another based on the electrodes' individual prediction performance. The best coefficients of determination for decoding hand trajectory in the two monkeys were 0.4815±0.0167 and 0.7780±0.0164. Performance results from individual ECoG electrodes showed that those with higher performance were concentrated at the lateral areas and areas close to the CS. The results of prediction according with different numbers of electrodes based on proposed methods were also shown and discussed. These results also suggest that superior decoding performance can be achieved from a group of effective ECoG signals rather than an entire ECoG array.
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影响因子：
3.7
作者：
Pistohl T;Schmidt TS;Ball T;Schulze-Bonhage A;Aertsen A;Mehring C
通讯作者：
Mehring C
DOI：
10.1073/pnas.1215092109
发表时间：
2012-10-16
影响因子：
11.1
作者：
Hauschild, Markus;Mulliken, Grant H.;Andersen, Richard A.
通讯作者：
Andersen, Richard A.
影响因子：
4
作者：
Kellis S;Miller K;Thomson K;Brown R;House P;Greger B
通讯作者：
Greger B
影响因子：
5.3
作者：
Fagg, Andrew H.;Hatsopoulos, Nicholas G.;Miller, Lee E.
通讯作者：
Miller, Lee E.
影响因子：
0.7
作者：
Hirata, Masayuki;Matsushita, Kojiro;Yoshimine, Toshiki
通讯作者：
Yoshimine, Toshiki