Human gait acquisition and analysis system and method based on inertial sensor information integration

Abstract

The invention relates to a human gait acquisition and analysis system and method based on inertial sensor information integration. The system comprises at least two IMU (Inertial Measurement Unit) sensors, two triaxial accelerometer sensors, a controller and an upper computer, wherein the two same IMU sensors are installed on a thigh and a shank of at least one side of a human body, are enabled to be coaxially and equidirectionally placed at outer side positions of the thigh and the shank, and are used for transmitting sensed accelerated speed and angular speed information of the thigh segment and the shank segment to the controller; the two same accelerometer sensors are coaxially and equidirectionally placed on a strip-shaped steel plate; an x-axis direction of a sensitive axis of each sensor is enabled to be parallel to the long edge of the steel plate, and a y-axis direction of the sensitive axis of each sensor is enabled to be parallel to the short edge of the steel plate; the strip-shaped steel plate is installed at the center position of a back of a waist part; the long edge of the steel plate is enabled to be parallel to a direction of a human spine, and the distance between the installation position to a hip joint rotary shaft is recorded; the accelerometer sensors are used for sensing the accelerated speed information of the human waist spine direction and transmitting to the controller; the controller and the upper computer accomplish classification of different gaits and carries out gait predication.

Description

technical field [0001] The invention relates to a human body gait acquisition and analysis system and method based on inertial sensor information fusion. Background technique [0002] The lower extremity exoskeleton for rehabilitation and assistance to the disabled and the military weight-bearing exoskeleton need to help the wearer walk and stand or assist the wearer to carry the load. The two should have a coordinated gait pattern. In order to achieve good gait tracking and control of the lower extremity exoskeleton and improve its dynamic stability, it is necessary to collect gait information and analyze the gait data classification, tracking and prediction of the wearer's gait data. [0003] (1) With the development of sensing technology and digital technology, there are more and more methods that can be used to detect human motion gait information. The commonly used methods mainly include image sequence analysis, EMG signal detection, angle / angular velocity detection and...

AI Technical Summary

Problems solved by technology

[0005] Image sequence analysis: real-time detection of gait data is costly, data processing is large, and delay is serious

[0006] EMG signal detection: The sensors and supporting devices used are expensive, and signal recognition and classification are difficult, and EMG signal detection is affected by the detection position, sweat, temperature, etc., and is easily interfered by signals, and the repeatability is not high

[0007] Angle / angular velocity detection: Due to the use of the integral algorithm, the error continues to accumulate, making the joint angle error gradually increase

[0008] Accelerometer detection method: only applicable to static calculation, not extended to dynamic joint angle calculation

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