Autonomous myoelectricity extraction method under condition of random dynamic parameter electrical stimulation

Abstract

The invention discloses an autonomous myoelectricity extraction method under the condition of random dynamic parameter electrical stimulation, which comprises the following steps of: shielding an electrical stimulation signal through a hardware circuit, performing empirical mode decomposition on the shielded signal xM+V (t) to obtain an intrinsic mode function set IMFm (t), splitting the intrinsicmode function set IMFm (t) by using a continuous window to obtain wIMFm, u (t), wherein m is an intrinsic mode function number, u is a window number, and the window length is about a current stimulation pulse period. Carrying out feature extraction for wIMFm, u (t). Carrying out threshold screening on the extracted feature to synthesize the required window, and taking the autonomous myoelectric signal after noise reduction. According to the invention, aiming at the defects of the prior stimulation noise removing technology, the influence of stimulus artifacts and the M wave is effectively removed through the combination of a hardware shielding and a software algorithm based on empirical mode decomposition.

Description

technical field [0001] The invention belongs to the technical field of rehabilitation medicine and the field of bioelectrical signal processing, and in particular relates to an autonomous electromyographic signal extraction method under the condition of dynamic parameter electric stimulation. Background technique [0002] The latest research report of the World Health Organization (WHO) shows that stroke has become the second leading cause of death in the world, and 6.7 million people died of stroke in 2012. In my country, up to now, the screening intervention program for high-risk groups of stroke has screened more than 6.1 million residents over the age of 40, and screened out more than 952,000 high-risk groups and patients of stroke, with a screening detection rate as high as 15.6%. Stroke is a major chronic disease that endangers the health of Chinese residents. With the development of modern medicine, the current 30-day survival rate of stroke is about 85%, and the 5-ye...

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Problems solved by technology

[0006] The present invention mainly aims at the defects of the existing stimulation noise removal technology, and proposes a method for detecting automyographic signals under the condition of random dynamic parameters (variable amplitude, variable frequency) functional electric stimulation, through hardware shielding and decomposition based on empirical mode Combined use of software algorithms to effectively remove the effects of stimulation artifacts and M-waves

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