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

Abstract

Human gait acquisition and analysis system and method based on inertial sensor information fusion, the system includes at least two IMU sensors, two three-axis accelerometer sensors, a controller, and a host computer; wherein two identical IMU sensors are installed on at least one side of the human body On the big and small legs, and ensure that the coaxial and same direction are placed on the outside of the thigh and the calf, it is used to transmit the acceleration and angular velocity information of the big and small legs that it senses to the controller; two identical accelerometer sensors are at the same time The axes are placed on a bar-shaped steel plate in the same direction, and the x-axis direction of the sensitive axis of the sensor is parallel to the long side of the steel plate, and the y-axis direction of the sensitive axis is parallel to the short side of the steel plate, and the strip-shaped steel plate is installed at the center of the waist and back, and Ensure that the long side of the steel plate is parallel to the direction of the human spine and record the distance from the installation position to the hip joint rotation axis, which is used to sense the acceleration information in the direction of the human waist and spine and transmit it to the controller; the controller and the host computer complete the classification of different stances and carry out Gait prediction.

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

Images