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A new approach to improve the quality of biosensor signals using Fast Independent Component Analysis: Feasibility study using EMG recordings

机译:使用快速独立成分分析提高生物传感器信号质量的新方法:使用EMG记录的可行性研究

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The proposed signal processing technique uses Fast Independent Component Analysis (ICA) algorithm to improve the quality of the original biosensors recordings, which can be used as valuable pre-processing technique such as cross talk removal, artefact reduction etc. Initially, the ill conditioned original surface Electromyography (sEMG) recordings were separated using ICA methods and later they were reconstructed using modified un-mixing matrix. The simulation results showed huge improvement of the original recorded signal after reconstruction. The proposed method has potential applications in various biomedical signal processing techniques.
机译:所提出的信号处理技术使用快速独立分量分析(ICA)算法来提高原始生物传感器记录的质量,可以用作有价值的预处理技术,例如串扰消除,伪像减少等。表面肌电图(sEMG)记录使用ICA方法进行分离,随后使用改良的非混合矩阵对其进行重建。仿真结果表明重建后原始记录信号的巨大改进。所提出的方法在各种生物医学信号处理技术中具有潜在的应用。

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