基于局部全通滤波器的时变延迟估计及其在表面肌电图中的应用

Christopher Gilliam, Adrian Bingham, T. Blu, B. Jelfs
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引用次数: 4

摘要

传导速度(CV)的估计是表面肌电图分析中的一项重要任务。这个问题可以被框定为电极记录之间的时变延迟(TVD)的估计。在本文中,我们提出了一种将多个电极的信息合并到单个TVD估计中的算法。该算法使用一个通用的全通滤波器在局部电平将两组信号关联起来。我们还通过提供一种从一组电极记录中识别神经支配区的自动方法来解决当前CV估计器的局限性,从而允许将整个阵列纳入估计。我们在合成和真实表面肌电信号数据上验证了该算法,结果表明该算法具有鲁棒性和准确性。
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Time-Varying Delay Estimation Using Common Local All-Pass Filters with Application to Surface Electromyography
Estimation of conduction velocity (CV) is an important task in the analysis of surface electromyography (sEMG). The problem can be framed as estimation of a time-varying delay (TVD) between electrode recordings. In this paper we present an algorithm which incorporates information from multiple electrodes into a single TVD estimation. The algorithm uses a common all-pass filter to relate two groups of signals at a local level. We also address a current limitation of CV estimators by providing an automated way of identifying the innervation zone from a set of electrode recordings, thus allowing incorporation of the entire array into the estimation. We validate the algorithm on both synthetic and real sEMG data with results showing the proposed algorithm is both robust and accurate.
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