Human body behavior identification method based on inertial sensor

An inertial sensor and recognition method technology, applied in the field of behavior recognition, can solve problems such as low classification accuracy, long training time, and complicated calculation process

Active Publication Date: 2015-01-07
DALIAN UNIV OF TECH
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Problems solved by technology

However, although the simple dimensionality reduction method in the prior art has high execution efficiency, its classification accuracy is low. Although the sequence forward selection algorithm has high classification accuracy, its calculation process is more complicated.
The classifier model method for obtaining human behavior in the prior art...

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  • Human body behavior identification method based on inertial sensor
  • Human body behavior identification method based on inertial sensor
  • Human body behavior identification method based on inertial sensor

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Embodiment Construction

[0035] In order to make the technical problems solved by the present invention, the technical solutions adopted and the technical effects achieved clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, but not to limit the present invention. In addition, it should be noted that, for the convenience of description, only parts related to the present invention are shown in the drawings but not all content.

[0036] figure 1 It is an implementation flowchart of the inertial sensor-based human behavior recognition method provided by the embodiment of the present invention. like figure 1 Shown, the human behavior recognition method based on inertial sensor that the embodiment of the present invention provides comprises:

[0037] Step 101, collect human body behavior data of n sensor no...

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Abstract

The invention provides a human body behavior identification method based on an inertial sensor. The method comprises the steps of acquiring human body behavior data of testees by means of the inertial sensor, conducting sliding window segmentation on the acquired human body behavior data, conducting feature extraction on a triaxial accelerated speed subsequence and a triaxial angular speed subsequence which are obtained after sliding window segmentation, conducting feature fusion on a feature vector to form a sample set of the human body behaviors of the testees, conducting feature selection on the sample set by means of the least correlated maximum redundant algorithm and the Bayes regularization sparse polynomial logistic regression algorithm, obtaining the classification feature vectors of all human body behaviors of all the testees, obtaining a classifier model of each human body behavior by means of a fuzzy least square support vector machine, and obtaining a human body behavior identification result after the human body behavior data are tested by means of the fuzzy least square support vector machine. By means of the human body behavior identification method, self-adaptation and identification efficiency can be improved.

Description

technical field [0001] The invention relates to the technical field of behavior recognition, in particular to a human behavior recognition method based on an inertial sensor. Background technique [0002] In the past 10 years, with the rapid development of MEMS (Micro-Electro-Mechanical System, MEMS) technology, sensors and mobile devices have unprecedented characteristics such as high computing power, small size and low cost, making these mobile devices Information interaction between equipment and people has become a part of daily life. The main purpose of pervasive sensing is to obtain data from sensors all over the place and extract useful information from them. In this field, the analysis and recognition of human behavior has become a hot research topic, which has an important role in promoting medical treatment, sports competition, military affairs, security, etc. [0003] Commonly used human behavior recognition has two different implementation forms, one is to use ...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06K9/46
CPCG06V40/23G06V40/28G06F18/2411
Inventor 王哲龙
Owner DALIAN UNIV OF TECH
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