Capacitive Touch Suppression Adaptation for Grounding Variations
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Solution Overview
Problem
Existing touch-sensitive input systems struggle to accurately differentiate between intended and unintended touch contacts due to similar signal characteristics, leading to false suppression of intended touches, especially under diverse operating conditions and environments, and variations in touch signal strength due to grounding conditions.
Innovation Solution
A method and apparatus for dynamically adjusting touch suppression based on contextual information and touch event features, using a suppression module that includes a feature extractor, machine-learned model, and classifier to adapt touch sensitivity in real-time, normalizing features for machine learning classifiers to enhance differentiation between intended and unintended touches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If touch suppression algorithms utilize features derived from signal strength to differentiate intended and unintended touch contacts, then the ability to suppress unintended touches is improved, but inconsistencies in performance occur due to variations in touch signal strength based on grounding conditions
Solution Approach 1:
The system dynamically adjusts the touch suppression threshold based on the detected grounding condition. When low grounding is detected, the threshold is adjusted to compensate for reduced signal strength, maintaining consistent performance across different operational environments. This dynamic adaptation resolves the contradiction by making the suppression algorithm flexible rather than static.
Solution Approach 2:
The invention changes the operational parameters of the touch suppression algorithm based on grounding conditions. By detecting the grounding state and adjusting relevant parameters (such as threshold values or weighting factors), the system maintains reliable touch contact differentiation across varying signal strength conditions without sacrificing suppression accuracy.
2Device complexity
If a single, static set of configurations is used to distinguish between various types of touch contacts, then the system complexity is reduced, but the system fails to accurately differentiate touch contacts across diverse operating conditions and environments
Solution Approach 1:
The system transitions from static configurations to dynamic adjustment based on detected grounding conditions. The touch suppression algorithm adapts its parameters in real-time based on the operational environment, maintaining high differentiation accuracy without requiring multiple fixed configuration sets. This resolves the contradiction by implementing conditional adaptability rather than full complexity.
Solution Approach 2:
The invention modifies key parameters of the touch suppression algorithm based on grounding condition detection. By changing thresholds, weighting factors, or other critical parameters according to the detected environment, the system achieves accurate touch contact differentiation across diverse conditions while maintaining relatively simple overall system architecture.
3Object-generated harmful factors
If touch suppression algorithms suppress unintended touch contacts, then false touches are reduced, but intended touch contacts may be falsely suppressed leading to suboptimal touch responsiveness
Solution Approach 1:
The system adjusts the suppression threshold parameter based on grounding conditions to prevent false suppression of intended touches. When low grounding is detected, the threshold is modified to account for reduced signal strength, ensuring that legitimate user inputs are not mistakenly suppressed while still blocking unintended contacts.
Solution Approach 2:
The touch suppression system incorporates feedback from grounding condition detection to continuously optimize its suppression behavior. By monitoring the operational environment and adjusting suppression parameters accordingly, the system maintains appropriate responsiveness to intended touches while effectively blocking false contacts, resolving the contradiction through adaptive feedback control.
Data Source
AI summary
A method for dynamically adjusting touch suppression on a capacitive touch screen of an electronic device is described. The method includes receiving touch screen data associated with a touch event and extracting a feature of the touch event. Contextual information related to the device's state is received, and based on both the feature and the contextual information, a touch sensitivity indicating a likelihood of the touch event being a user input is determined. A touch suppression of the capacitive touch screen is then adjusted based on the determined touch sensitivity, changing touch performance by distinguishing intended user inputs from unintended touch contacts.