Three-dimensional gait information collection and analysis method based on Kinect motion-sensing technology

Abstract

Provided is a three-dimensional gait information collection and analysis method based on Kinect motion-sensing technology. The method includes the steps of utilizing a running machine, a Kinect sensor, a Kinect supporting cloud platform and a computer to constitute a gait data collection hardware system, choosing a speed level of the running machine for a person to walk on the running machine; using the Kinect sensor to identify nodes of a human skeleton, and adopting threshold filtering and double-exponential filtering to stabilize data about the skeleton nodes, then building a local coordinate system according to human anatomy and calculating an anatomy movement curve; using a catch method for a gait event to identify the gait event, finishing calculation of gait parameters according to the gait skeleton data, and finally displaying the gait parameters and a gait motion curve on the interface. The three-dimensional gait information collection and analysis method based on the Kinect motion-sensing technology has the advantages of low production costs, no use of gauge points for catching three-dimensional skeleton nodes, remote collection, an ability of automatically catching a gait event, precise calculation of gait parameters and tracks, simple operation and the like.

Description

technical field [0001] The invention relates to the technical field of gait data acquisition and analysis in clinical medicine, in particular to a three-dimensional gait information acquisition and analysis method based on Kinect somatosensory technology. Background technique [0002] Walking and its gait are reflected at the biomechanical level under the control of the central nervous system. Normal gait depends on the coordination of the central nervous system, peripheral nervous system and musculoskeletal system. When the normal physiological functions and mutual coordination and balance of the muscles, ligaments, bones, joints, brain, spinal cord, and peripheral nerves of the lower limbs are damaged, various degrees of abnormal gait can be caused. The collection and analysis of gait information is to assist doctors in It is an important tool for the quantification of patients' rehabilitation assessment, training planning, disease diagnosis, and prosthetic fitting. [00...

AI Technical Summary

Problems solved by technology

The wearable inertial sensor test method needs to use the gyroscope and the accelerometer at the same time to capture the human body movement process. When determining the movement process in the human body world coordinate system, the algorithm is complex and the motion trajectory calculated is low in accuracy. At the same time, the wearing of wearable test equipment The process is complicated, the experiment is not strictly repeatable, and it is difficult to monitor the anatomical position of the joint

The plantar pressure test method can detect the change of plantar pressure over time, and can realize simple gait phase changes. However, this method cannot record the entire cycle of gait movement, because the swing phase in gait movement is in the Carried out in the air, there is no contact with the ground at this time, the complete cycle cannot be captured, and the plantar force capture information is single, the gait capture time is short, and the gait information cannot be completely recorded

The EMG test method is aimed at the detection of the lower extremity muscles. This method tests the gait from the implicit information, and requires a macrosc

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