Gait type identification method based on three-axis acceleration sensor and neural network

Abstract

The invention discloses a gait type identification method based on a three-axis acceleration sensor and a neural network. The method specifically comprises steps as follows: step 1), establishing a database of gait acceleration signals; step 2), performing the segmentation stage of the signals in the corresponding period; step 3), removing a gravity factor; step 4), performing the gait feature extraction stage; step 5), performing gait presorting stage; step 6), performing dimensionality reduction operation of a gait feature set; and step 7), performing specific gait identification stage. According to the method, gait features are screened with a staged MIV (mean impact value) method, the gait type identification work is performed in combination of a BP (back propagation) neural network, the extracted features are taken as input independent variables of the neural network, six gait types of sitting, standing, walking in a low speed, walking in a high speed, going upstairs and going downstairs are effectively identified sequentially through the gait presorting stage and the specific gait identification stage, and the method can have higher accuracy and reliability through enlarging of a gait data capacity range and the optimized design of the neural network.

Description

Technical field [0001] The invention belongs to the technical field of biomedical signal processing, and relates to a gait type identification method, in particular to a gait type identification method based on a three-axis acceleration sensor and a neural network. Background technique [0002] Gait refers to the posture of a person when walking, which is a complex biological feature. It has the following advantages: it does not require high system resolution, is suitable for long-distance recognition, is not vulnerable to infringement, and is difficult to hide. Therefore, the research on gait has become one of the research hotspots of domestic and foreign research institutions and universities. [0003] Foreign research and attention on gait type identification started early, and the methods are mainly based on two modes of video image and sensor. [0004] Based on the research method of video images, the experimental data comes from the camera to monitor the individual's movement...

AI Technical Summary

Problems solved by technology

[0009] (1) In terms of the wearing position of the sensor, the wearing position must be determined uniformly and attached to the clothing, which will make some experimenters uncomfortable during the experiment and make the gait unnatural;

[0010] (2) Segmenting the signal in chronological order will separate the sudden action signal at a certain moment, which will affect misjudgment;

[0012] (4) Some feature dimensionality reduction methods are not effective in screening gait signal features, and the discrimination rate is not high

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