Touch Panel Stylus Detection Using Dynamic Noise Ripple Thresholds
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Solution Overview
Problem
Existing touch panel systems face challenges in accurately identifying stylus positions due to noise interference from liquid crystal modules (LCM), as the noise threshold values are difficult to set correctly, leading to incorrect identification of sensed signals.
Innovation Solution
A method that reads capacitance variation values and employs a preset noise ripple value to differentiate between stylus and noise signals by comparing the difference values between sensed units, determining if the capacitance variation value of a unit is higher than adjacent units, thereby accurately identifying stylus positions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fixed noise threshold value is preset to deduct LCM noises, then the influence of LCM noises is avoided, but the true capacitance variation values of stylus may be incorrectly identified as noises due to fluctuating noise levels
Solution Approach 1:
The patent transitions from a static fixed threshold approach to a dynamic adaptive threshold approach. The noise threshold is no longer fixed but adapts based on the actual noise characteristics and capacitance variation patterns. This allows the system to maintain reliable noise filtering while preserving accurate stylus detection by adjusting the threshold according to fluctuating noise levels and signal characteristics.
Solution Approach 2:
The patent changes the parameter of noise threshold from a constant value to a variable parameter that reflects actual noise conditions. By making the threshold dynamic and adaptive, the system can accommodate varying noise levels without misidentifying stylus signals as noise, thus resolving the contradiction between reliable noise filtering and precise stylus detection.
2Reliability
If a relatively low constant noise threshold value is preset, then LCM noises are effectively filtered, but true touched points of the stylus may be ignored due to fluctuating noise levels
Solution Approach 1:
The system employs dynamic threshold adjustment that responds to actual signal conditions. Instead of using a low constant threshold that may inadvertently filter valid stylus signals, the adaptive threshold rises and falls with the noise characteristics, ensuring that true stylus touches are not missed while still effectively filtering LCM noises.
Solution Approach 2:
The patent implements feedback mechanisms that continuously monitor signal characteristics and adjust the noise threshold accordingly. This feedback loop allows the system to learn from actual usage patterns and noise conditions, maintaining effective noise filtering while preserving accurate stylus touch detection through iterative adjustment.
3Measurement precision
If the capacitance variation values are compared with adjacent units to identify stylus, then the slopes of stylus signals are utilized for identification, but additional processing steps are required
Solution Approach 1:
The patent segments the touch panel into multiple sensed units and compares capacitance variation values between adjacent units. This segmentation approach allows the system to identify stylus signals through local comparisons of signal slopes, improving precision while distributing the processing complexity across multiple manageable units rather than requiring a single complex processing step.
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 method effectively filters out LCM noise and correctly identifies stylus positions by utilizing the higher slopes of stylus signals, enhancing the precision of touch panel systems.
Implementation Method 1
capacitance variation values, dVstylus and dVfinger are equal to a base value subtracted by the capacitance values of true respective sensed signals of a stylus and a finger therefrom
Implementation Method 2
When a touch panel is mounted on a liquid crystal module (LCM), noises are generated because of the scanning of the scan lines on the LCM
Data Source
AI summary
A method for identifying touch object on a touch panel has steps of (A) reading m capacitance variations on a first direction, wherein the m capacitance variations respectively correspond to m sensed units of the touch panel; (B) determining whether a difference between the capacitance variation of a kth sensed unit and that of another sensed unit exceeds a preset noise ripple, wherein k is equal to or smaller than m, m is a positive integer; (C) determining whether the capacitance variation of the kth sensed unit exceeds those of the adjacent sensed units; and (D) determining a touch stylus touched on the touch panel when the difference exceeds the preset noise ripple and the capacitance variation of the kth sensed unit exceeds those of the adjacent sensed units. Accordingly, the method can correctly identify a range touched by a stylus from the sensed signals combined with LCM noise signals.