Context-Aware Touch Classification for False Grip Rejection
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Solution Overview
Problem
Touch-screen devices, particularly in handheld form factors with minimal bezels, often register false touch events due to inadvertent contact from gripping, leading to degraded user experience and increased noise in touch signals.
Innovation Solution
A capacitive touch sensor system that integrates context data from the operating system, including device orientation and user interface layout, to classify valid touch regions using a touch-classifier system, reducing false positives and improving accuracy by rejecting invalid touch events early in the processing pipeline.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the touch sensor registers all contact on the display surface, then no valid touch input is missed, but false touch events from gripping increase
Solution Approach 1:
The system performs preliminary classification of touch regions by comparing touched regions against UI element locations before processing touch events. This preliminary action filters out false touches from gripping areas (bezel, edges) that do not correspond to valid UI elements, while preserving genuine user inputs that do match UI elements.
Solution Approach 2:
The patent introduces an intermediary classification layer between the touch sensor and the operating system. This intermediary system uses context data about UI element positions to mediate between raw touch signals and processed touch events, determining whether each touched region corresponds to a valid UI element before forwarding the event.
2Reliability
If all touch regions are processed by the operating system, then all potential valid inputs are handled, but processing latency increases
Solution Approach 1:
The system extracts and filters out invalid touch events (those not corresponding to UI elements) before they reach the operating system. By taking out these false positives early in the processing pipeline, the OS only processes genuine user inputs, reducing overall processing latency while maintaining completeness for valid touches.
Solution Approach 2:
The touch classifier performs preliminary processing and validation of touch events before they are passed to the operating system. This preliminary action includes comparing touched regions with UI element locations and filtering out invalid events, so the OS receives only pre-validated touch inputs that require processing.
3Ease of operation
If the device processes every touch event, then user experience is maintained, but power consumption increases
Solution Approach 1:
The system extracts and eliminates invalid touch events (false positives from gripping) before they are processed further. By removing these unnecessary processing steps for invalid touches, the system reduces power consumption while maintaining proper handling of all valid user inputs, thus preserving user experience.
Solution Approach 2:
The touch classifier performs partial processing of touch events by only fully processing those that match UI elements. For regions clearly identified as invalid (bezel, edges), minimal processing is performed, reducing energy expenditure while maintaining adequate response for genuine user interactions.
4Area of stationary object
If the touch sensor covers the entire display area, then maximum touch coverage is achieved, but noise from non-functional areas increases
Solution Approach 1:
The system performs preliminary identification of non-functional areas (bezel, edges) and marks them as invalid touch regions. This preliminary action allows the system to maintain full sensor coverage for maximum touch capability while filtering out noise from areas that cannot contain valid UI elements.
Solution Approach 2:
An intermediary classification layer is introduced that uses context data about functional vs. non-functional display areas to filter touch signals. This mediator determines whether touched regions in non-functional areas should be processed, reducing noise from gripping while preserving full sensor coverage.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Reduces false positives and latency in touch detection while minimizing power consumption by distinguishing valid from invalid touch inputs based on context data, enhancing user experience and efficiency.
Implementation Method 1
a capacitive touch sensor system that integrates context data from the operating system
Data Source
AI summary
A method to provide classified touch data to a computer program executing on a device comprises: (a) assembling a map of touch signal from a touch sensor arranged on an electronic display and including a plurality of crossings of row and column electrodes, the map including a corresponding touch-signal value for each of the plurality of crossings, and defining at least one touched region of the touch sensor; (b) serving context data relating to user-interface content currently presented on the electronic display; (c) computing classified touch data corresponding to the map of touch signal, based at least partly on the map and the context data; and (d) providing the classified touch data to an operating system of the device.