Adaptive Touch Sensing Filter for Noise Reduction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional touch sensing systems using the electrostatic capacity method are sensitive to external noise, leading to high error rates in environments with heavy noise, and existing noise removal techniques like median filtering and IIR filtering are not adaptable to multiple environments and insufficient for accurate touch coordinate detection.
Innovation Solution
A touch sensing method that calculates a filtering coefficient using the equation W(n) = I(n) - F(n-1)R, where R is a scale constant, to adaptively filter sensing signals, and includes condition processes to determine when to apply filtering based on reference values, ensuring accurate touch coordinate detection even in noisy environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional electrostatic capacity method is used for touch sensing, then the system can detect touch positions, but the system becomes sensitive to external noise causing high error rates in noisy environments
Solution Approach 1:
The patent implements dynamic filtering by adaptively adjusting the filtering coefficient W(n) based on the relationship between current sensing signal I(n) and previous output signal F(n-1). The filtering strength varies dynamically according to signal conditions rather than using a fixed filtering parameter, allowing the system to maintain accuracy while adapting to different noise levels in the environment.
Solution Approach 2:
The patent changes the filtering parameter W(n) dynamically based on signal conditions. The filtering coefficient is calculated as W(n) = I(n) - F(n-1)R, where R is a scale constant. This parameter adaptation allows the filtering mechanism to respond to varying noise conditions, reducing noise sensitivity while preserving touch detection accuracy.
2Object-affected harmful factors
If fixed value filtering (median filtering or IIR filtering) is applied to remove noise, then noise removal capability is improved, but adaptability to multiple environments deteriorates
Solution Approach 1:
The patent transforms fixed-value filtering into a dynamic filtering system where the filtering coefficient W(n) changes adaptively based on the relationship between current sensing signal I(n) and previous output signal F(n-1). This dynamic adjustment enables the same filtering mechanism to perform effectively across multiple environments with varying noise characteristics.
Solution Approach 2:
The patent incorporates feedback by using the previous output signal F(n-1) in the calculation of the current filtering coefficient W(n). This feedback mechanism allows the system to learn from past signal conditions and adjust its filtering behavior accordingly, improving adaptability to different environmental conditions while maintaining noise removal capability.
3Ease of operation
If center of gravity method is used to detect touch coordinates, then coordinate detection is simplified, but noise cannot be sufficiently removed
Solution Approach 1:
The patent applies preliminary filtering action before coordinate detection. By dynamically filtering the sensing signals using the adaptive coefficient W(n) before processing coordinates, the system removes noise interference in advance, allowing the subsequent coordinate detection (whether using center of gravity or other methods) to operate on cleaned signals, thus maintaining both simplicity and noise rejection.
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
The method achieves high touch sensitivity and accurate touch coordinate detection in noisy environments by adaptively filtering signals, reducing noise interference and improving system reliability.
Implementation Method 1
a change in electrostatic capacity generated when a human hand or an object contacts the touch screen is detected to correspond to a touch position
Data Source
AI summary
A touch sensing method for a touch screen including an image display device with a touch-sensitive screen. The method includes a filtering process that includes calculating an output signal of an nth frame from a sensing signal of the nth frame output from a touch sensing unit configured to sense touches of the touch-sensitive screen, the calculating using an equationF(n)=I(n)×W(n)+F(n−1)×[1−W(n)],wherein F(n) represents the output signal of the nth frame, I(n) represents the sensing signal of the nth frame, F(n−1) represents an output signal of an (n−1)th frame, and W(n) represents a filtering coefficient; and outputting the output signal of the nth frame to an output end. The filtering coefficient is calculated by an equationW(n)=I(n)-F(n-1)R,wherein R is a scale constant. The touch sensing method has high touch sensitivity in an environment with heavy noise while being capable of correctly detecting touch coordinates.