Instantaneous myoelectricity image based gesture identification method

Abstract

The invention discloses an instantaneous myoelectricity image based gesture identification method. During a training stage, firstly instantaneous myoelectricity signals acquired by array electrodes are preprocessed and arranged according to electrode positions to form an instantaneous myoelectricity image; and secondly an image classifier such as a deep convolutional neural network is trained by using the instantaneous myoelectricity image and a gesture tag corresponding to the instantaneous myoelectricity image to obtain network model parameters. During a test stage, firstly to-be-identified instantaneous myoelectricity signals acquired by the array electrodes are preprocessed and arranged according to the electrode positions to form the instantaneous myoelectricity image; and secondly the trained model parameters are substituted into the classifier to identify the gesture tag corresponding to the instantaneous myoelectricity signals. According to the instantaneous myoelectricity image based gesture identification method, a gesture can be quickly and accurately identified based on the instantaneous myoelectricity image and an image classification method. No literature for gesture identification by the instantaneous myoelectricity signals exists at home and abroad yet.

Description

technical field [0001] The invention belongs to the field of combining computer and biological signals, and specifically uses an image classifier represented by a deep convolutional neural network to recognize gestures corresponding to instantaneous myoelectric images extracted from instantaneous myoelectric signals. Background technique [0002] With the rapid development of new technologies such as computer vision, touch interaction, and perceptual computing, perceptual user interface (PUI) has become one of the research focuses in the field of human-computer interaction. Perceptual user interface is a highly interactive and multi-channel user interface based on the interaction between people and the real world. Its goal is to make human-computer interaction and human-real world interaction consistent. Reach the realm of intuitive and natural interaction. In order to enable computers to better judge and understand human interaction intentions, "integration of life, machin...

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Problems solved by technology

There is no literature at home and abroad using instantaneous EMG signals for gesture recognition

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