Individual rehabilitation motion trajectory planning system based on non-contact human body data acquisition

Abstract

The invention discloses an individual rehabilitation motion trajectory planning system based on non-contact human body data acquisition, which mainly solves the problems of inaccurate data and incomplete functions of the existing human body data acquisition system, and comprises a human body data acquisition module, a data calculation and storage module and a data remote sharing module. The human body image acquisition module acquires human body color and depth images and transmits the images to the data calculation and storage module; the data storage module adopts a local computer and comprises different functional sub-modules which are respectively used for completing image registration, human body personality data resolving and sending, rehabilitation motion track planning and data storage work; the data remote sharing module remotely receives human body personality data and rehabilitation motion trails, and the data and the trails are reproduced on a remote computer in numerical character, oscillogram, video and animation modes. The collected human body data are real and reliable, personalized rehabilitation movement tracks can be planned for patients, and the method can be used for remote online rehabilitation guidance of dyskinesia patients.

Description

technical field [0001] The invention belongs to the field of computer images, and particularly relates to an individual rehabilitation motion trajectory planning system, which can be used for remote online rehabilitation guidance for patients with movement disorders. technical background [0002] With the aggravation of population aging in my country and the increasing number of patients with movement disorders, human movement rehabilitation has gradually become the focus of social attention. In the field of sports rehabilitation, in the process of using rehabilitation robots to help the human body carry out rehabilitation training, human data collection and rehabilitation trajectory planning are very important links. On the one hand, the collection of human body data can help the rehabilitation specialist to understand the current motor function and state of the patient’s body, which is convenient for formulating a rehabilitation plan; basis in order to better help patient...

AI Technical Summary

Problems solved by technology

[0003] The existing human body data collection methods mainly include three categories: first, use wearable structures to fix sensors around the human body, and collect fixed parameters and motion states of the human body according to the motion state of the human body. The disadvantage of this method is that the wearable structure It will affect the user's experience, and it is more inconvenient to fix the sensor for those with injured limbs; the second type is based on optical motion capture, by pasting reflective markers on the human body, and using multiple infrared cameras to detect and track the movement of the markers , to synthesize the movement data of the marker points into the movement data of the human body. The disadvantage of this method is that each experiment requires complex calibration of the camera group, and the whole set of equipment is expensive and poor in portability; the third method uses image detection The method uses a camera to capture the movement process of the human body and conduct motion analysis. The disadvantage of this method is that it does not rely on two-dimensional image coordinates for safety, lacks information in the depth direction, and cannot accurately calculate the real data of the human body. The result may be Invalid, cannot provide reasonable data support for trajectory planning

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