Knee joint disease prediction apparatus and system

Abstract

The invention discloses a knee joint disease prediction apparatus and system. The system comprises an acquisition unit used for acquiring gait data and establishing a gait database; a preprocessing unit used for preprocessing the gait data in the gait database and obtaining standard gait data; a model training unit used for constructing a multilayer neural network model, training the multilayer neural network model according to the standard gait data, and obtaining a trained neural network model; and a prediction unit used for acquiring the gait data of users in need of detection, inputting the data to the trained neural network model, and obtaining a prediction result. According to the apparatus and system, multiple multilayer neural network models are established and trained through thegait data, knee joint diseases can be further predicted, various knee joint diseases can be rapidly and accurately predicted without radiation, and the prediction efficiency is greatly improved. The apparatus and system can be widely applied to the medical field.

Description

technical field [0001] The invention relates to the technical field of medical information decision-making, in particular to a knee joint disease prediction device and system. Background technique [0002] The knee joint is one of the largest joints in the whole body. It is composed of the femur, tibia and patella. It is the weight-bearing joint of the human body and one of the most vulnerable joints. The knee joint is the joint with the highest incidence rate in the whole body, and the prevalence of knee joint diseases in the Chinese population is as high as 150 million. Knee joint diseases mainly include: osteoarthritis, meniscus injury, cruciate ligament injury, synovitis, patella softening, etc. The main symptoms are knee joint pain and joint dysfunction, not only related to various lesions in the joint, but also often caused by various extra-articular factors. Moreover, the symptoms produced by the knee joint are often not specific. Symptoms such as pain, limp legs, ...

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Problems solved by technology

[0004] 1. There is a certain amount of radiation in the early warning and prediction method that relies on traditional imaging equipment. At present, traditional imaging equipment mainly includes X-ray, CT, MRI, and ultrasound. damage the body or aggravate the condition of the knee joint;

[0005] 2. The prediction method relying on traditional imaging equipment can only detect the static state of the knee joint, and cannot reflect the functional state and motion status of the knee joint

Traditional imaging equipment cannot dynamically detect this type of disease, so it cannot predict the disease from the perspective of motor function, ignores the abnormal motor function of the patient, and can also lead to wrong prediction or missed knee joint disease;

[0006] 3. The early warning and prediction method relying on traditional imaging equipment cannot quickly warn and predict knee joint diseases, which takes more than 30 minutes, and usually requires professionally trained imaging personnel to analyze the inspection results

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