Artificial-intelligence-based eyelid movement function evaluation system

Abstract

The invention discloses an artificial-intelligence-based abnormal eyelid movement evaluation system. The system comprises an examined object obtaining module, an eye and specific part positioning module, a TSN model, a probability output module and an evaluation module; the examined object obtaining module is used for obtaining a facial video which is obtained from a facial movement video of the input examined object and only contains the examined object, the eye and specific part positioning module is used for positioning the eye and specific part of the facial video and obtaining an eye movement video and a specific part linkage video which only contain the examined object, the TSN model is used for processing the eye movement video and the specific part linkage video and outputting movement signals of eyes and specific parts, the probability output module is used for outputting probability signals appearing when a computer judges that eyelid movement is abnormal in each frame, and the evaluation module is used for obtaining the abnormal level according to the probability signals appearing in abnormal eyelid movement and an abnormal eyelid movement probability judging mechanism.Accordingly, universal acceptability, convenience, accuracy, objectivity and repeatability are achieved, and the clinical applicability is high.

Description

technical field [0001] The present invention relates to the field of evaluation of abnormal degree of eyelid movement, and more particularly relates to an artificial intelligence-based eyelid movement function evaluation system. Background technique [0002] Existing techniques for observing eyelid movement abnormalities mainly include neuromuscular recorder technology, brainstem magnetic resonance angiography (MRA) examination, and wearing new glasses that record the frequency function of eyelid movement. The disadvantages of neuromuscular recorder technology are that the technical operation is complicated, time-consuming and labor-intensive, and the cooperation degree is low for the elderly and children; Therefore, the measurement results are easily affected by the subjective factors of the testers, the results lack repeatability and stability, and it is difficult to carry out early inspections on a large scale in the population. Brainstem magnetic resonance angiography (...

AI Technical Summary

Problems solved by technology

[0009] The purpose of the present invention is to solve the technical problems that the existing abnormal eyelid movement detection equipment has high requirements for the test environment, detection equipment and detection personnel, the cost of manpower and material resources is high, and the detection results are one-sided and not accurate enough; Acceptability, convenience, objectivity, accuracy and repeatability, clinically usable eyelid motor function assessment system based on artificial intelligence

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