An auxiliary screening system for tic disorder based on video data

Abstract

The invention discloses an auxiliary screening system for tic disorder based on video data, which uses video data to automatically identify tic symptoms, uses a three-dimensional convolutional neural network based on multi-instance learning, and uses a combination of three-dimensional channel attention and three-dimensional spatial attention modules to The features learned by the three-dimensional convolutional neural network are optimized, and the loss function is optimized by using time smoothing constraints, which can improve the model's ability to detect tics, and combine the health information questionnaire data transformed from clinical inquiries to form an auxiliary screening system for tics, which improves Screening and identification efficiency, and reduce the stress and discomfort of patients in unfamiliar environments through non-direct contact. The present invention simplifies the most time-consuming symptom observation process through video data collection and twitch detection, and through data fusion analysis and visualization, provides screening patients with preliminary cognition of diseases, and also provides references for doctors' follow-up diagnosis and treatment and basis.

Description

technical field [0001] The invention relates to the technical field of medical and health information, in particular to an auxiliary screening system for tic disorder based on video data. Background technique [0002] According to the "Expert Consensus on the Diagnosis and Treatment of Children's Tic Disorders (2017 Practical Edition)" proposed by the Neurology Group of the Pediatrics Branch of the Chinese Medical Association [1] , when a person is before the age of 18, exhibits multiple movements and one or more vocal tics at the same time within a year, while excluding other medical diseases (such as encephalitis after viral infection, etc.) or substance influence (such as cocaine, etc.) Tourette syndrome (TS) can be diagnosed when the patient is diagnosed, and the continuous observation and inspection part of the conversation will take a long time. However, children are generally restless by nature, and it is difficult for parents to pay attention to the symptoms of tics...

AI Technical Summary

Problems solved by technology

[0004] According to the existing diagnosis process, the doctor needs to spend a long time to observe and confirm the patient's tic characteristics, and needs to inquire with the patient and family members to confirm the recent and previous tic characteristics, eating habits, living habits, family medical history, etc.; During the diagnosis process, the patient may have an inhibitory state due to going to a new environment or coming into contact with strangers, which is not conducive to the actual diagnosis and evaluation of the disease.

At present, the tic symptoms of tic patients mainly rely on the complex process based on the clinical diagnosis of tic disease, and many tic patients have problems that are not easy to detect. However, the existing tic detection methods rely on deep brain stimulation or wearable devices to collect data, and the data collection method is relatively complex

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