Touch Sensor Noise Filtering via Threshold Compensation
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Solution Overview
Problem
Conventional noise filtering algorithms for touch screens reduce the number of sensing data samples, leading to a decrease in signal-to-noise ratio (SNR) due to the deletion of minimum and maximum values, which affects the sensing performance.
Innovation Solution
A noise filtering method that profiles noise in sensing data and compensates it to keep values near or within the calculated maximum and minimum thresholds based on the average value of the previous frame, rather than deleting them, thereby maintaining more data samples and improving SNR.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If the conventional noise filtering algorithm deletes minimum and maximum values of aligned sensing data, then impulse noise is suppressed, but the number of data samples is reduced and signal-to-noise ratio decreases
Solution Approach 1:
The patent changes the parameter handling approach from deletion to transformation. Outlier values are transformed into valid range values through linear interpolation using neighboring valid points, preserving the sample count while removing noise. This parameter transformation resolves the contradiction by maintaining both noise suppression and sufficient sample size for accurate measurement.
Solution Approach 2:
The patent converts harmful outlier values into beneficial valid data points. Instead of discarding minimum and maximum values as noise, the method transforms them into interpolated values that fall within the valid range, thereby converting potentially harmful data into useful information that maintains signal-to-noise ratio while still suppressing impulse noise effects.
2Object-affected harmful factors
If the conventional noise filtering algorithm deletes minimum and maximum values of aligned sensing data, then impulse noise is suppressed, but the number of data samples is reduced
Solution Approach 1:
The patent changes the parameter handling approach from deletion to transformation. Outlier values are transformed into valid range values through linear interpolation using neighboring valid points, preserving the sample count while removing noise. This parameter transformation resolves the contradiction by maintaining both noise suppression and sufficient sample size for accurate measurement.
3Reliability
If the sensing data is compensated to be near maximum or minimum threshold, then the data is maintained within valid range, but additional processing complexity is introduced
Solution Approach 1:
The patent implements a self-service mechanism where the filtering algorithm uses the data's own structure (neighboring valid points) to correct outliers. The linear interpolation automatically determines correction values based on local data patterns, making the system self-adapting and reducing the need for external parameter tuning or complex control logic.
Solution Approach 2:
The patent changes the parameter handling approach from deletion to transformation. Outlier values are transformed into valid range values through linear interpolation using neighboring valid points, preserving the sample count while removing noise. This parameter transformation resolves the contradiction by maintaining both noise suppression and sufficient sample size for accurate measurement.
Data Source
AI summary
An electronic device with a touch sensor comprises: a touch screen including touch sensors defined by Tx lines and Rx lines; a touch sensing circuit that supplies a drive signal to the Tx lines and senses a voltage change in the touch sensors to output sensing data; and a noise filtering unit that profiles the type of noise in the sensing data and compensates the sensing data so that the sensing data is near the maximum threshold or the minimum threshold, which is calculated based on a average value of the previous frame, or within the range between the maximum and minimum thresholds.