Inadvertent Touch Input Classification via Contextual Analysis
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Solution Overview
Problem
As computing devices increasingly incorporate touch surfaces and other input methods, there is a growing need to accurately distinguish between intentional and unintentional user inputs to prevent unintended actions and enhance user experience.
Innovation Solution
The implementation of a classification system that utilizes contextual information, such as touch contact location, keyboard input history, and additional information like duration and velocity, to classify user inputs as intentional or unintentional, allowing the device to refrain from performing actions triggered by unintentional contacts and potentially recall incorrect actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the device responds to all touch contacts on the touch surface, then the responsiveness and user interaction capability is improved, but inadvertent inputs (such as palm rests while typing) trigger unintended actions reducing reliability
Solution Approach 1:
The system performs preliminary classification of touch contacts using contextual information (location, keyboard input history, duration, velocity) before executing actions. This preliminary analysis allows the device to distinguish intentional from inadvertent inputs in advance, preventing unintended actions while maintaining responsiveness to valid inputs
Solution Approach 2:
The system uses contextual feedback from multiple sources including keyboard input history, touch location data, contact duration, and velocity information to continuously refine its classification of user inputs. This feedback mechanism enables the system to adapt its response based on the current operational context, improving both responsiveness and input accuracy
2Reliability
If the device implements a classification system using contextual information to distinguish intentional from unintentional inputs, then input accuracy is improved, but the device complexity increases due to additional sensors and processing requirements
Solution Approach 1:
The system uses existing sensors and components (touch surface, keyboard, processors) for multiple purposes. The touch surface not only detects touch contacts but also provides location and duration information. The keyboard serves both as an input device and a contextual indicator for determining whether a touch is inadvertent. This multi-functionality reduces the need for additional dedicated components
Solution Approach 2:
The system leverages its own operational data (keyboard input history, current application state, touch patterns) to classify inputs without requiring external assistance or additional specialized sensors. The existing system components serve themselves by providing contextual information that the classification algorithm uses to distinguish intentional from unintentional inputs
Data Source
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AI summary
Techniques for identifying inadvertent user input, such as inadvertent touch contact or air input, are described. The techniques may include classifying a touch contact or air input as intentional or unintentional based on contextual information related to the touch contact, the air input, or a device via which the touch contact or air input was received. In some examples, the contextual information may indicate how a user is interacting with the device, such as a position of the user's hand, a location of the touch contact on a touch surface, a path of user's touch trajectory, an application with which the user may be interacting, keyboard input history of the user, and so on. When the user input is classified as unintentional, the techniques may refrain from performing an action that is generally triggered by the user input.