Glove Touch Detection via Multi-Scan Sensitivity Adjustment
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Solution Overview
Problem
Conventional capacitance sensing systems struggle to accurately detect gloved touches on touch-sensitive devices, often resulting in false detections and inability to handle multiple touches, while requiring users to remove their gloves for interaction.
Innovation Solution
The implementation of a glove touch detection tool that performs multiple scans with varying sensitivity parameters to differentiate between gloved and ungloved touches, allowing for accurate detection and reporting of gloved touches without impacting finger or stylus detection performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional capacitance sensing systems use standard detection thresholds, then ungloved touches can be detected, but gloved touches result in false detections or are missed entirely
Solution Approach 1:
The system dynamically adjusts detection thresholds and sensitivity parameters based on the detected touch pattern. When a gloved touch is detected (identified by specific capacitance change patterns), the system adapts its detection parameters to maintain accurate tracking, transitioning between different detection modes to handle both ungloved and gloved interactions reliably
Solution Approach 2:
The system changes detection parameters including sensitivity levels, threshold values, and scan configurations to differentiate between gloved and ungloved touches. By modifying these parameters dynamically, the system can accurately detect capacitive changes caused by gloved fingers while filtering out false detections from hovering or approaching objects
2Measurement precision
If the system increases sensitivity to detect gloved touches, then gloved touch detection improves, but false detections during hovering or approaching events increase
Solution Approach 1:
The system segments the detection process into multiple independent scan passes with different sensitivity levels. A first pass uses higher sensitivity to detect potential gloved touches, while subsequent passes use lower sensitivity to confirm actual touches and filter false detections. This segmentation allows the system to maintain high detection accuracy without increasing false positives
Solution Approach 2:
The system uses feedback from multiple scan passes to verify touch events. Detection results from one scan are used to adjust parameters for subsequent scans, allowing the system to distinguish between genuine gloved touches and false detections from hovering objects by analyzing the consistency and pattern of capacitive changes across multiple measurements
3Measurement precision
If the system performs multiple scans with varying sensitivity, then detection accuracy improves, but processing time and complexity increase
Solution Approach 1:
The system performs multiple scans but only processes results from scans that detect significant capacitive changes. By using conditional processing based on detection thresholds, the system avoids unnecessary computation in scans that would not contribute to accurate detection, reducing overall processing complexity while maintaining high detection accuracy
Solution Approach 2:
The system performs a preliminary scan with higher sensitivity to identify potential gloved touches before conducting confirmation scans. This preliminary action allows the system to pre-process and filter data, reducing the computational burden on subsequent scans by focusing processing resources only on regions of interest where actual touches are likely to occur
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
Enables users to interact with touch-sensitive devices while wearing gloves, reducing the need for frequent glove removal and enhancing accuracy and reliability in detecting both gloved and ungloved touches, with no false detections during approaching or hovering events.
Implementation Method 1
Capacitance sensing systems can sense electrical signals generated on electrodes that reflect changes in capacitance. Such changes in capacitance can indicate a touch event (i.e., the proximity of an object to particular electrodes).
Data Source
AI summary
Apparatuses and methods of glove touch detection are described. One method performs a first scan to detect an object proximate to a sense array. The first scan comprises a first sensitivity parameter. The method compares touch data from the first scan against a plurality of thresholds. The method performs a second scan to detect a touch event when the first scan's touch data exceeds a glove saturation threshold of the plurality of thresholds. The second scan comprising a second sensitivity parameter that is different than the first sensitivity parameter. The method reports a glove touch event when the first scan's touch data does not exceed the glove saturation threshold and exceeds a glove-reporting threshold of the plurality of thresholds.