Teaching window control method and device

Through multimodal sensors and quantum annealing optimization technology, the limitations of traditional teaching window control methods in real-time cognitive adaptation and cross-terminal consistency are solved, and the efficient, real-time layout optimization of teaching windows and multi-device collaborative display are achieved, improving user experience and computing efficiency.

CN120353360AActive Publication Date: 2025-07-22BEIJING HUACAN ELECTRONICS CO LTD
4 Cites 2 Cited by

Patent Information

Application Number
CN202510846109.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-06-24
Publication Date
2025-07-22
Estimated Expiration
2045-06-24

AI Technical Summary

Technical Problem

Traditional teaching window control methods have significant limitations in real-time cognitive adaptation, large-scale layout optimization, dynamic constraint balance and cross-terminal perceptual consistency, and it is difficult to meet the needs of diversified teaching content and multi-device collaboration.

Method used

Through multimodal sensors, eye tracking data, EEG signals and teaching semantic flow intensity are collected in real time, and multimodal perceptual data input source is built, combining quantum annealing optimization module and xinjiang geometric manifold correction to achieve dynamic layout optimization of the teaching window, and color consistency and tactile feedback are ensured through a multi-terminal rendering engine.

Benefits of technology

The precise fit between the teaching window layout and learners' cognitive load is achieved, the response delay is reduced to 200ms, the calculation speed is accelerated by 3 orders of magnitude, the layout distortion rate is reduced by 87%, the cross-screen color jump problem is eliminated, and the user experience is improved.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The invention relates to the field of education, and discloses a teaching window control method which comprises the following steps: synchronously acquiring eye movement tracking data, electroencephalogram signals and teaching semantic flow intensity in real time through a multi-modal sensor to form a multi-modal perception data input source; inputting the multi-modal perception data into a quantum annealing optimization module, constructing a Hamiltonian model based on semantic coupling strength and physical display constraints, and generating a window layout candidate parameter set in parallel; and performing symplectic geometry manifold correction on the candidate parameter set, calculating a physical adaptability boundary of the compensation display device through a differential geometry contact coefficient, and screening out a feasible solution space meeting curvature constraint. According to the method, the eye movement track and the electroencephalogram characteristics are fused through the multi-mode sensing unit, real-time layout optimization driven by the cognitive state is achieved, the limitation of separation of physiological signals and interface design is broken through, and window arrangement is made to accurately accord with the instantaneous cognitive load level of a learner.
Need to check novelty before this filing date? Find Prior Art