Spatial Filtering Touch Signal Noise Cancellation
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Solution Overview
Problem
Current data communication systems face challenges in effectively processing and interpreting sensor signals from touch screens, particularly in distinguishing between desired and undesired touches, which affects the accuracy and reliability of touch detection and processing.
Innovation Solution
The implementation of a spatial filter active noise cancellation (ANC) circuit and adaptive filter techniques in conjunction with drive-sense circuits to enhance the signal-to-noise ratio and improve touch detection by processing capacitive images from touch screens, allowing for better identification of touch locations and types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional touch detection methods are used, then the system is simple and easy to manufacture, but the accuracy of distinguishing desired touches from undesired touches deteriorates
Solution Approach 1:
The patent segments the touch detection process into multiple processing stages: raw signal acquisition from capacitive sensors, spatial filtering to remove noise patterns, and classification to distinguish desired vs undesired touches. This segmentation enables high measurement precision through systematic noise reduction while keeping each processing stage manageable and implementable with standard computational resources.
Solution Approach 2:
The patent introduces spatial filters as intermediary processing elements between the raw sensor signals and the final touch classification. These filters act as mediators that selectively attenuate noise components (such as those from nearby objects or environmental interference) while preserving genuine touch signals, thereby improving detection accuracy without requiring complex hardware modifications.
2Reliability
If spatial filtering and adaptive filter techniques are implemented, then the signal-to-noise ratio improves, but the processing time and computational resources increase
Solution Approach 1:
The patent applies spatial filtering and adaptive noise cancellation as preliminary processing steps before touch classification and interpretation. By pre-processing the signals to remove noise and enhance quality upfront, the system reduces the computational burden on subsequent processing stages, thereby minimizing overall processing time while maintaining high signal-to-noise ratios throughout the detection pipeline.
Solution Approach 2:
The adaptive filter techniques employed in the patent operate periodically, updating filter coefficients based on incoming signal characteristics while maintaining continuous noise suppression. This periodic adaptation allows the system to respond dynamically to changing noise conditions without requiring continuous heavy computation, thus balancing reliability improvement with acceptable processing time.
3Reliability
If advanced signal processing techniques are used to identify touch locations and types, then the reliability of touch detection improves, but the device complexity increases
Solution Approach 1:
The patent implements multi-functional signal processing circuits that perform multiple tasks: spatial filtering, noise cancellation, touch location detection, and touch type classification. By designing processing units that can execute multiple functions within a single integrated system, the patent improves detection reliability across various touch scenarios without proportionally increasing device complexity. The same hardware infrastructure supports diverse processing needs through software or configurable logic.
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
This approach significantly improves the accuracy of touch detection and processing by reducing noise interference and enhancing the signal quality, enabling more reliable identification of desired touches and ignoring undesired inputs, thus improving the overall performance of touch screen systems.
Implementation Method 1
spatial filter active noise cancellation (ANC) circuit and adaptive filter techniques to enhance the signal-to-noise ratio
Implementation Method 2
processing capacitive images from touch screens
Data Source
AI summary
A method for execution by a touch screen computing device includes obtaining a touch signal associated with a row electrode of a touch screen display that is operable to render frames of data into visible images, where the touch screen display includes rows of electrodes oriented with columns of electrodes. The method further includes spatial filtering the touch signal in a first direction of the row electrode with respect to columns of the electrodes that form intersections with the row electrode to produce first direction touch signal data. The method further includes spatial filtering the touch signal in a second direction of the row electrode with respect to the intersections to produce second direction touch signal data. The method further includes combining the first and second direction touch signal data to produce a filtered touch signal. The method further includes processing the filtered touch signal to determine touch data.