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Gait recognition method based on inertial sensor

An inertial sensor and gait recognition technology, applied in the field of body area network, can solve problems such as the influence of the accuracy of gait recognition methods, and achieve the effect of reducing the amount of calculation

Active Publication Date: 2015-06-24
DALIAN UNIV OF TECH
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  • Summary
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In the process of implementing the above gait recognition method, there are still some problems that are difficult to solve, such as selecting which signals to collect, how to determine the size of the time window and the elements of the feature vector, and which classification algorithm to choose, etc.
These problems will affect the accuracy of the gait recognition method

Method used

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  • Gait recognition method based on inertial sensor
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  • Gait recognition method based on inertial sensor

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Embodiment Construction

[0043] The specific embodiments of the present invention will be described in detail below in combination with the summary of the invention and the accompanying drawings.

[0044] The gait recognition method based on inertial sensors includes four stages: data acquisition, period division, feature extraction and gait classification. The process of this method is as follows: figure 1 shown.

[0045] (1) Data collection stage

[0046] Five sensor nodes and one base station are used as hardware devices for data collection. The sensor node consists of four parts: sensor module, wireless communication module, processor module and power module. The sensor module integrates three sensors: gyroscope, accelerometer and electronic compass, which are respectively responsible for collecting angular velocity, acceleration and magnetic field strength, and converting them from physical quantities to electrical signals; the wireless communication module uses nRF24L01 wireless transceiver, w...

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Abstract

The invention belongs to the field of the body area network and relates to a gait recognition method based on an inertial sensor. The method includes four phases. In the data acquisition phase, four sensor nodes attached to legs of a testee and a sensor node attached to the waist of the testee are used to acquire motion angular speeds, accelerations and magnetic field strengths of the legs and waist of the body of the testee and wirelessly transmit data to a base station, and then the data are transmitted to the upper computer for processing. In the period dividing phase, gait periods are divided according to angular speed change curves of the shanks so as to obtain segment data corresponding to gaits. In the feature extraction phase, waveform features and behavioral features are extracted from the segment data and used to describe fluctuation of sensor signals and sport performance of gait behaviors. In the gait classification phase, the gait features are transmitted to a classifying model, types of the gaits are acquired by computing, and thus gait recognition is achieved. The method is suitable for use in gait recognition in the fields, such as sports training, medical care and game design.

Description

technical field [0001] The invention belongs to the field of body area network and relates to a gait recognition method based on an inertial sensor. Background technique [0002] Gait recognition research is a branch of the body area network field, which plays an important role in disease diagnosis, sports training and human-computer interaction. There are two main types of current gait recognition methods: computer vision-based methods and inertial sensor-based methods. The former needs to be limited to use in a specific environment where the camera is arranged, the equipment cost is high, and it is not conducive to protecting personal privacy. With the development of body area network technology, more and more researches use wearable sensors instead of cameras to recognize gait. This method perceives motion behavior through the inertial sensor worn on the human body, which is relatively cheap, and is not limited by the monitoring scene and time, and has a broader applica...

Claims

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Application Information

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IPC IPC(8): G01C21/16
CPCG01C21/16
Inventor 赖晓晨周国乔周忠隋海波赵钰
Owner DALIAN UNIV OF TECH
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