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System and method for human body movement identification of combined sensor

A technology for combining sensors and recognizing human body, applied in the field of sensor application, can solve the problems of data error, inability to realize data collection and action recognition, leakage of personal privacy of the detector, etc., and achieve the effect of reliable signal

Inactive Publication Date: 2013-09-25
WUHAN TEXTILE UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, video-based recognition systems are usually only capable of video capture and recognition at locations where specific cameras are installed because the cameras are installed in fixed locations
The human body is a moving object. When the detected person leaves the detectable range of the video camera, the system cannot realize data collection and action recognition.
In addition, light and reflection can also cause data errors, and may also cause leakage of personal privacy to the detected person

Method used

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  • System and method for human body movement identification of combined sensor
  • System and method for human body movement identification of combined sensor
  • System and method for human body movement identification of combined sensor

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0032] Embodiment 1: A system for combining sensors to recognize human actions

[0033] The system is a system based on the combination of inertial sensors and flexible sensors to recognize human actions. Its structure is as follows: figure 1 As shown, it includes: a data acquisition module for collecting human motion signals; a power supply module for supplying power to make the module work normally; a signal conditioning module for data signal processing; a microcontroller module for controlling and coordinating the entire system ; A wireless communication sending module and a wireless communication receiving module for transmitting data to the motion analysis machine, and a motion analysis machine for motion comparison.

[0034] The data acquisition module ( figure 1 ), the inertial sensor 3 ( figure 2 ) and flexible sensor 1, flexible sensor 2, flexible sensor 4 and flexible sensor 5 placed at the elbow joint and knee joint ( figure 2 ), which are respectively connect...

Embodiment 2

[0043] Example 2: Fabrication of Flexible Sensors

[0044] The fabrication of the flexible sensor is divided into the following four steps:

[0045] Step 1: Composition

[0046] Including copper foil sheet 1 / 4"x4.5", cellulose acetate strip 1 / 4"x4.5"x0.01" (thickness), heat shrink tubing 3 / 8" (diameter) x5", resistive material 5 / 16" x 5".

[0047] Copper foil sheet: Industrial copper foil sheet is used to make flexible circuits. There is a thin layer of copper wrapped around a plastic such as a cellulose acetate strip. Using single-sided copper, the copper foil wrapped material is copper on one side and plastic on the other side. Cut the material into long strips of 4.5" wide and 1 / 4" with scissors. Solder 6" of wire on the bottom of each.

[0048] Resistance material: Cloth, plastic and paper are optional. Here conductive black plastic polyethylene tape is used. The single-layer bag made of carbon-containing polyethylene does not change its conductivity under changes ...

Embodiment 3

[0063] Embodiment 3: The method of combining sensors to recognize human body movements

[0064] The system for recognizing human body motions using the above-mentioned combined sensors can recognize six daily human body motions, which include walking, running, jumping, falling, standing and sitting. It is suitable for the monitoring of patients in physical rehabilitation and the daily life of the elderly.

[0065] The method is: placing the inertial sensor 3, the flexible sensor 1, the flexible sensor 2, the flexible sensor 4 and the flexible sensor 5 on different parts of the human body ( figure 2 ). Place the inertial sensor 3 directly in front of the waist of the human body ( figure 2 ), to obtain the inertial data in the process of human body movements, and obtain the parameters of human body movement conditions; place the flexible sensors 1-1, 1-2 and the flexible sensors 2-1, 2-2 in pairs on the inner and outer sides of the human elbow joint ( image 3 ), the flexib...

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Abstract

The invention relates to a system and a method for human body movement identification of a combined sensor. The system comprises a power supply module, a data acquisition module, a signal processing module, a micro-controller module, a wireless communication module and a movement analysis machine, wherein the power supply module is used for supporting the normal working of the system, the data acquisition module is used for acquiring human body movement signals and is composed of an inertia sensor which is horizontally placed on the front portion of the waist of a human body and a flexible sensor which is placed on the elbow and the knee of the human body, the signal processing module is used for processing data signals and is respectively connected with the inertial sensor and the flexible sensor through leads, the micro-controller module is used for controlling and coordinating the entire system, the wireless communication module is used for transmitting data to the movement analysis machine, and the movement analysis machine is used for movement contrast and is a computer with a built-in movement identification model. The method is the identification of six kinds of daily human movement of walking, running, jumping, falling, standing and sitting with the system. The system and the method for the human body movement identification of the combined sensor are reliable to use, can be used for obtaining movement information of human torsos, and have the advantages of being simple and convenient.

Description

technical field [0001] The invention relates to the field of sensor applications, in particular to a system and method for recognizing human body movements based on inertial sensors and flexible sensors. Background technique [0002] Human action recognition technology is mainly based on two types of methods: recognition systems based on video images and systems based on wearable sensors. [0003] The video image-based recognition system uses one or several video cameras to capture human body motion images, and through a specially designed image processing algorithm, determines human body motion and human motion status. However, the video-based recognition system can only perform video capture and recognition only at the place where a specific camera is installed because the camera is installed in a fixed location. The human body is a moving object. When the detected person leaves the detectable range of the video camera, the system cannot realize data collection and action...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F3/01G06F3/0346
Inventor 吴雨川肖子明薛勇佘风华胡峰李颖
Owner WUHAN TEXTILE UNIV
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