Feedback control method based on sensor fusion and operation intention recognition

By fusing inertial measurement, pressure sensing, and external visual posture data, multidimensional features are extracted and operational intentions are identified to generate interest weight coefficients. This solves the problem of lag in the feedback process in existing technologies and realizes dynamic feedback control of intelligent interactive devices.

CN122450291APending Publication Date: 2026-07-24HUBEI ZELIN EDUCATION TECHNOLOGY GROUP CO LTD
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Patent Information

Application Number
CN202610515014.X
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-04-17
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

Existing intelligent interactive early childhood teaching aids or toys lack the ability to align and jointly model multi-source heterogeneous data over time, making it difficult to extract high-dimensional features that reflect operational behavior, accurately identify operational intentions, and resulting in a delayed feedback process and a lack of dynamic adjustment capabilities.

Method used

By acquiring inertial measurement data, pressure sensing data, and external visual attitude data, a multimodal operation data sequence is formed after preprocessing. Multidimensional feature parameters are extracted by performing sliding window segmentation processing, and operation intentions are identified by combining multidimensional decision mapping. Interest weight coefficients are generated to construct a feedback control strategy.

Benefits of technology

It enables refined identification of complex operational behaviors, improves the timeliness of feedback strategies and the continuity of interactive responses, and transforms the feedback process from passive triggering to proactive adjustment based on changes in interest.

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Abstract

The invention provides a feedback control method based on sensor fusion and operation intention recognition, and relates to the technical field of intelligent sensors, the method comprises the following steps: obtaining inertial measurement data, pressure sensing data and external visual attitude data arranged in a target interaction carrier, and executing preprocessing to form a multi-modal operation data sequence; sliding window segmentation processing is executed based on the multi-modal operation data sequence, and multi-dimensional feature parameters reflecting operation intensity, change trend and periodic characteristics are extracted to construct feature vectors; performing multi-dimensional decision mapping on the feature vectors to identify corresponding operation intention categories; an interest weight coefficient is generated according to the operation intention category and the continuous distribution characteristics of the operation intention category in the time dimension; and constructing a feedback control strategy based on the interest weight coefficient and the operation intention category, and driving an execution unit to output a response signal. The multi-source data of the interactive equipment can be fused, and the timeliness of dynamic adjustment of the feedback strategy is improved in combination with operation intention recognition.
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