Abstract Decoding using Bayesian Muscle Activation Estimators.
Abstract Decoding using Bayesian Muscle Activation Estimators.
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使用贝叶斯肌肉激活估计器进行抽象解码。
DOI：
10.1109/embc.2018.8512663
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Dyson M
中科院分区：
文献类型：
--
作者：
Dyson M
在使用肌电抽象解码器时，将两个递归贝叶斯肌肉激活估计器与标准线性滤波进行了比较。解码器由手部固有肌肉控制。在这两个实验中，线性滤波器在总体得分方面都优于贝叶斯方法。贝叶斯肌肉解码器对肌肉活动变化的响应速度更快，并有望显著提高解码器的整体通信速率。
Two recursive Bayesian muscle activation estimators were compared against standard linear filtering during use of a myoelectric abstract decoder. The decoder was controlled by intrinsic muscles of the hand. In both experiments the linear filter outperformed the Bayesian methods in terms of general score. The Bayesian muscle decoders were faster to respond to changes in muscle activity and show promise for significantly enhancing overall decoder communication rate.