Support vector machine-based pedestrian gait classifying system and method

A technology of support vector machine and classification system, applied in the field of real-time classification of pedestrian gait, can solve the problems of inaccurate and representative results, and achieve the effect of improving positioning accuracy

Active Publication Date: 2015-02-04
SHANGHAI JIAO TONG UNIV
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Problems solved by technology

Therefore, the analysis of data in the time domain by the above-mentioned technolo

Method used

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  • Support vector machine-based pedestrian gait classifying system and method
  • Support vector machine-based pedestrian gait classifying system and method
  • Support vector machine-based pedestrian gait classifying system and method

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Experimental program
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Embodiment 1

[0039] Such as figure 1 As shown, the implementation method of this embodiment includes the following steps:

[0040] Step 1. Training data collection. The gait information of pedestrian walking and running is obtained as the original training data by using the training stage data acquisition module installed on the pedestrian's foot.

[0041] The data acquisition module in the training phase includes: an accelerometer and a gyroscope. The foot movement information includes the triaxial acceleration and triaxial angular velocity signals generated by the pedestrian's foot during movement. Therefore, there are six sets of raw training data for each class of gait. The original training data for each type of gait contains only one kind of gait, that is, pure walking or pure running data.

[0042] Step 2, training data processing. Use the data processing module in the training phase to process the training data, specifically:

[0043]2.1) Sampling point selection: Extract the...

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Abstract

The invention discloses a support vector machine-based pedestrian gait classifying system and a support vector machine-based pedestrian gait classifying method. The system comprises a data acquiring module, a data processing module and an SVM (Storage Virtualization Management) module, wherein the SVM module is provided with a storage medium; the data acquiring module acquires gait training data and transmits the gait training data to the data processing module to be processed; the data processing module outputs the input quantity of the acquired gait training data to the SVM module to be studied to obtain an SVM classifier which is then stored in the storage medium; during real-time test, after real-time gait information is acquired in real time by the data acquiring module, data processing is preformed by the data processing module to acquire the input quantity of the test data; the input quantity of the test data is classified by the SVM module according to the SVM classifier to obtain real-time gait type. A static interval in a pedestrian moving process can be precisely detected by the system and the method, and the positioning precision is improved.

Description

technical field [0001] The present invention relates to a technique in the technical field of inertial navigation, in particular to a system and method for realizing real-time classification of pedestrian gait by using a Support Vector Machine (Support Vector Machine, SVM). Background technique [0002] The purpose of gait classification is to classify pedestrian gait into walking and running categories, and use more reasonable and efficient detection methods for different gaits in pedestrian inertial navigation. In the field of pedestrian inertial navigation, the static detection method for pedestrian walking is not suitable for running gait, so the running positioning accuracy under the same detection method is low. Effective identification of running gait will help to adopt more targeted static detection methods and improve the positioning accuracy of pedestrian inertial navigation algorithms. [0003] SVM is a linear classifier based on statistical learning theory. Its...

Claims

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Application Information

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IPC IPC(8): A61B5/11
CPCA61B5/112
Inventor 吴哲君唐雷赵忠华
Owner SHANGHAI JIAO TONG UNIV
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