Filtering method for electromyographic signals based on experience pattern decompositions

Abstract

The invention provides a filtering method for electromyographic signals based on experience pattern decompositions. The method comprises following steps: collecting multiple electromyographic signals and forming electromyographic signal samples by sampling electromyographic signals in multiple detection channels according to sampling windows and sampling steps of time lengths; decomposing electromyographic signal samples according to an experience mode decomposition method into multiple intrinsic mode functions IMF and decomposition reminders; and selecting at least one intrinsic mode functions IMF for add refactoring and obtaining electromyographic signals without interference.The filtering method for electromyographic signals based on experience pattern decompositions has following beneficial effects: defects of a digital filter are solved; and therefore, filtering wave can filter all useful electromyographic signals and cannot be too deep or insufficient by man-made configurations.

Description

technical field [0001] The present invention relates to a preprocessing algorithm for myoelectric signals, in particular to a method for filtering myoelectric signals based on empirical mode decomposition, specifically to a filtering algorithm for power frequency interference, motion artifacts and baseline drift in myoelectric signals, and its application fields include Myoelectric signal processing, gesture recognition, myoelectric prosthetics, rehabilitation engineering, biomechanics and other fields. Background technique [0002] Wearable devices, especially those based on the principle of myoelectric signals, have gradually attracted public attention and acceptance. Myoelectric signals have experienced nearly a hundred years of development since they were applied in the field of control, and have been researched and applied in the fields of medical diagnosis and biomechanics. With the development of biomedical technology and artificial intelligence technology, the metho...

AI Technical Summary

Problems solved by technology

The digital filter method is mature, but the disadvantages are also obvious: the digital filter has a wide filtering frequency band, and while filtering out interference, it is bound to filter out useful myoelectric signals; Filtering too deep or not enough

These defects will affect the subsequent analysis and identification of the signal

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