Leveraging inactive touchpoints for gesture recognition and user interface configuration

By using a machine learning model to generate a hand model and filter out false inputs, the computing device effectively addresses the challenge of differentiating between intentional and unintentional inputs, leading to improved user interaction accuracy and consistency.

WO2025071578A1 Publication Date: 2025-04-03GOOGLE LLC
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Patent Information

Application Number
PCT/US2023/034225
Authority / Receiving Office
WO · WO
Patent Type
Applications
Current Assignee / Owner
Filing Date
2023-09-29
Publication Date
2025-04-03

AI Technical Summary

Technical Problem

Computing devices with presence-sensitive housings struggle to differentiate between intentional gesture inputs and unintentional inputs caused by a user holding or adjusting their grip on the device, leading to potential misinterpretation of user interactions.

Method used

A computing device employs a machine learning model, such as a federated machine learning model, to generate a hand model based on inputs detected by the presence-sensitive housing. This model helps identify which inputs are part of a gesture and filters out false inputs, improving the accuracy of user input recognition.

Benefits of technology

The solution enables the computing device to accurately identify gesture inputs, reducing the likelihood of mistakenly recognizing unintentional inputs. This results in a more consistent and reliable user experience by filtering out irrelevant inputs and enhancing the precision of user interactions.

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Abstract

A method comprises detecting, by a presence-sensitive housing, one or more user inputs. The method further comprises generating, by a computing device, a map of the one or more user inputs, wherein the map indicates respective locations of the presence-sensitive housing at which each of the one or more user inputs was detected. The method further comprises generating, by the computing device, a model of a hand by at least applying a machine learning model to the map of the one or more user inputs. The method further comprises removing, by the computing device and using the model of the hand, at least one user input that is not consistent with a gesture input from the one or more user inputs to generate a filtered set of user inputs. The method further comprises determining, by the computing device and based on the filtered set of user inputs, the gesture input.
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