A gesture recognition method and system for a power distribution automation terminal touch screen

By collecting and processing electric field distribution data on the surface of the touch screen and utilizing asynchronous acceleration technology of deep and shallow electrode arrays, the problems of gesture recognition delay and uncertainty in existing technologies have been solved, achieving low-latency and highly stable gesture recognition effects, and improving the real-time performance and reliability of touch interaction.

CN121879616BActive Publication Date: 2026-06-30ZHEJIANG HANPU POWER TECH CO LTD +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
ZHEJIANG HANPU POWER TECH CO LTD
Filing Date
2026-03-20
Publication Date
2026-06-30

AI Technical Summary

Technical Problem

Existing predictive gesture recognition technologies suffer from signal blind spots when faced with weak electric field excitation, resulting in recognition delays and uncertainties, and failing to achieve efficient and stable gesture recognition in high-concurrency scenarios.

Method used

By collecting electric field distribution data on the surface of the touch screen, asynchronous acceleration processing of deep and shallow electrode arrays is used to extract gesture action features and perform amplitude and frequency joint correction to achieve asynchronous accelerated sampling and voltage regulation. Finally, clock alignment and voltage write-back operations are performed on multiple target processing units to output gesture recognition results.

Benefits of technology

It achieves low-latency and high-stability gesture recognition even when the finger is not in contact, improving the real-time performance and reliability of touch interaction, reducing the false recognition rate and trajectory jumps, and improving the system response speed.

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Abstract

This invention relates to a gesture recognition method and system for a touchscreen of a power distribution automation terminal. The method includes: acquiring electric field distribution data provided by a deep electrode array; extracting gesture action features and performing amplitude-frequency joint correction based on a preset electric field strength benchmark to obtain a compressed delay time; sampling the deep and shallow electrode arrays of the touchscreen accordingly to obtain asynchronous accelerated sampling data; adjusting the deep electrode output voltage according to the deep electric field change parameters in the asynchronous accelerated sampling data until the deep electric field change parameters converge, and determining the recognition delay compression value; calculating gesture recognition optimization parameters from the compression value and the converged electric field distribution data, and performing timing alignment and voltage write-back on multiple target processing units, finally outputting the gesture recognition result. This invention enables low-latency, high-stability gesture recognition when a user's finger approaches the touchscreen, improving the real-time performance and reliability of touch interaction.
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