Touch Screen Pixel Coordinate Validation and Noise Reduction
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Solution Overview
Problem
Existing touch-screen display systems face inefficiencies in generating accurate pixel coordinate estimates due to noise corruption, require user-interactive calibration, and struggle with detecting the absence of touch, leading to potential false touches and increased sampling delays.
Innovation Solution
A calibrated touch-screen display system that automatically recalibrates itself in real-time using digital signals from the touch-screen, employing an 8-wire configuration with shunts and pre-defined sampling rates to minimize noise and sampling delays, and detect 'no touch' states without user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If timing delays are inserted into the sampling process to allow drivers to settle out, then noise corruption of coordinate estimates is reduced, but sampling speed and productivity are decreased
Solution Approach 1:
The system performs preliminary calibration actions by storing reference coordinate data from known touch locations and pre-calculating correction factors. This preliminary preparation allows the system to quickly adjust for drift and noise without requiring lengthy real-time settling delays, thus maintaining both accuracy and sampling speed.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring coordinate estimates against stored reference data and adjusting subsequent measurements based on detected drift patterns. This feedback loop enables the system to compensate for noise and drift in real-time without requiring prolonged settling periods, resolving the contradiction between precision and productivity.
2Measurement precision
If calibration routines require user assistance by touching known locations, then measurement precision is improved, but ease of operation and device complexity are worsened
Solution Approach 1:
The system performs self-calibration by automatically detecting touch events at known reference locations and updating its own correction factors without requiring user intervention. The system monitors its own performance drift and adjusts calibration parameters autonomously, eliminating the need for users to manually touch known locations while maintaining coordinate accuracy.
Solution Approach 2:
The system uses feedback from automatic touch detection at reference locations to continuously refine calibration parameters. By monitoring its own measurement deviations and automatically adjusting correction factors, the system maintains high measurement precision while completely eliminating the need for user-assisted calibration procedures.
3Device complexity
If only active touch is detected, then device complexity is reduced, but reliability is worsened due to false touches from noise
Solution Approach 1:
The system performs preliminary validation by comparing detected touch coordinates against stored reference data and correction factors before accepting the touch event. This preliminary check filters out false touches caused by noise while maintaining simple detection hardware, as the validation is performed through software comparison rather than additional physical sensors.
Solution Approach 2:
The system implements feedback validation by continuously comparing current touch detections against reference patterns and adjusting detection thresholds based on detected noise levels. This feedback mechanism enables the system to distinguish between valid touches and noise-induced false touches without adding complex detection hardware, thus maintaining simplicity while improving reliability.
4Productivity
If x-axis position is validated before y-axis position generation, then productivity is improved by avoiding invalid y-axis estimates, but device complexity increases due to additional validation logic
Solution Approach 1:
The validation logic is segmented into independent modular functions, with x-axis validation and y-axis validation handled as separate but coordinated processes. This segmentation allows the system to efficiently validate coordinates in a structured manner without creating complex intertwined logic, as each axis validation can be independently optimized and maintained.
Solution Approach 2:
The system performs preliminary x-axis validation before proceeding to y-axis estimation, using pre-stored reference data and correction factors to quickly determine validity. This preliminary action filters out obviously invalid measurements early in the process, improving productivity by avoiding wasted computation on invalid y-axis estimates while maintaining simple validation logic through early filtering.
Data Source
AI summary
An enhanced touch-screen display system is disclosed for generating pixel coordinate estimates corresponding to a location on a display screen touched by a user. The system is an analog resistive touch-screen display system having a processor and associated software algorithms to allow for the calibration and validation of pixel coordinate estimates as an integral part of the real-time generation of the pixel coordinate estimates. Multiple calibrated pixel coordinate estimates are generated and processed at a pre-defined sampling rate to determine a valid pixel position to minimize sampling delays due to settling times. The x-axis position is also validated before the system attempts to generate a y-axis position to avoid the wasted time for generating y-axis estimates when x-axis estimates are corrupted. Noisy estimates are inherently reduced in the touch-screen display system by providing shunts across certain drivers in the system that also allow for detection of a “no touch” state.