Touch Sensor Fluid Detection via Dynamic Sensitivity Switching
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Solution Overview
Problem
Existing touch sensors struggle to accurately differentiate between fluid contact and intentional touch inputs, leading to potential malfunctions and distorted touch position recognition.
Innovation Solution
The electronic device adjusts touch sensitivity based on pattern recognition of node values representing fluid contact on the touch sensor, using a neural network to identify and compensate for fluid-induced distortions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If touch sensitivity is increased to improve touch input detection, then touch input recognition accuracy is improved, but fluid contact causes false touch recognition and distorted position detection
Solution Approach 1:
The touch sensor system dynamically adjusts its sensitivity threshold based on detected conditions. When fluid contact is detected through pattern recognition of node values, the system lowers the touch sensitivity threshold to prevent false touch recognition. This dynamic adaptation allows the system to maintain high touch input recognition accuracy while preventing fluid-induced false detections.
Solution Approach 2:
The system introduces an intermediary detection layer that analyzes patterns in node values to distinguish between intentional touch inputs and fluid contact. By examining the spatial distribution and magnitude of node value changes across multiple nodes, the system can identify characteristic patterns of fluid contact and differentiate them from genuine touch inputs, thereby maintaining reliability without sacrificing sensitivity.
2Reliability
If touch sensitivity is decreased to prevent fluid contact false recognition, then false touch recognition is reduced, but intentional touch input detection accuracy deteriorates
Solution Approach 1:
The system dynamically adapts its sensitivity threshold based on real-time detection of fluid contact conditions. When fluid is detected through pattern analysis of node values, the system automatically adjusts to a lower sensitivity mode to prevent false recognition. When no fluid is present, the system operates at higher sensitivity to ensure accurate touch detection. This dynamic adjustment resolves the contradiction by making sensitivity context-dependent rather than fixed.
Solution Approach 2:
The system changes the operational parameters of the touch sensor based on detected conditions. Specifically, it modifies the sensitivity threshold parameter and potentially the sampling frequency or analysis window based on whether fluid contact is detected. This parameter adaptation allows the system to optimize performance for each operational context, maintaining both reliability and accuracy.
3Measurement precision
If pattern recognition algorithms are added to identify fluid contact, then fluid detection accuracy is improved, but device complexity increases
Solution Approach 1:
The fluid detection function is segmented into a separate, dedicated processing module that operates independently from the main touch input processing pipeline. This segmentation allows the system to implement sophisticated pattern recognition algorithms for fluid detection without significantly complicating the overall system architecture. The segmented approach enables modular development and maintenance while achieving high fluid detection accuracy.
Solution Approach 2:
The system uses a simplified model or copy of the touch sensor data structure to perform fluid detection analysis, rather than directly processing the full complexity of raw sensor signals. By creating an intermediate representation or simplified copy of the node value patterns, the system can apply pattern recognition algorithms more efficiently with reduced computational overhead, thereby limiting the increase in device complexity.
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
Enhances the accuracy of touch input recognition by reducing sensitivity when fluid is detected, thereby minimizing malfunctions and maintaining precise touch position detection.
Implementation Method 1
The touch sensor may identify the contact based on a capacitive method
Implementation Method 2
The touch sensor may identify the contact based on a resistive method
Data Source
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AI summary
Provided is an electronic device. The electronic device comprises a display; a touch sensor disposed in the display and including a plurality of lines and a plurality of nodes formed by the plurality of lines; a memory storing instructions; and a processor. When executed by the processor, the instructions cause the electronic device to: acquire a plurality of node values from the plurality of nodes, respectively; change the touch sensitivity of the touch sensor from a first touch sensitivity to a second touch sensitivity lower than the first touch sensitivity on the basis of identifying a pattern of the plurality of node values; and on the basis of identifying a change in the pattern of the plurality of node values, identify whether to recognize a contact on the touch sensor as a touch input through a plurality of line values acquired from the plurality of lines, respectively.