Touch Panel Controller Position Detection Accuracy
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Solution Overview
Problem
Existing touch panel systems face challenges in accurately detecting the position of external objects due to sparse sensor distribution, leading to non-constant velocity display of touch paths and interference between close touches, which results in inaccurate position detection and non-linear touch traces.
Innovation Solution
A controller that performs self-capacitance detection followed by mutual-capacitance detection to reduce misjudgments in close touch positions and achieve more accurate position detection, while also enabling palm rejection by neglecting wide-range touches during self-capacitance detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If sensors are sparsely disposed on the touch panel, then device complexity is reduced and manufacturing cost is lowered, but measurement precision deteriorates leading to non-constant velocity display of touch paths
Solution Approach 1:
The patent introduces differential sensing information as an intermediary between the sparsely disposed sensors and the final position detection. By calculating differential values between adjacent sensor signals, the system creates additional measurement points that effectively increase sensor density without adding physical sensors, thereby resolving the contradiction between device complexity and measurement precision
Solution Approach 2:
The patent segments the touch detection process into multiple stages: first obtaining raw sensor signals, then calculating differential sensing information between adjacent sensors, and finally using this segmented information to determine touch position. This segmentation allows the system to extract more position information from the same sparse sensor array, improving measurement precision without increasing device complexity
2Device complexity
If self-capacitance detection is used for position detection, then device complexity is reduced and response speed is improved, but reliability deteriorates due to interference between close touches and inability to reject palm touches
Solution Approach 1:
The patent transitions from single-dimension self-capacitance detection to two-dimension mutual-capacitance detection by introducing both first sensing information (from first sensors) and second sensing information (from second sensors). This dimensional expansion allows the system to distinguish between close touches and palm touches by analyzing the spatial relationship between different sensor signals, thereby improving reliability without significantly increasing device complexity
3Ease of manufacture
If sensors are sparsely disposed on the touch panel, then manufacturing cost is reduced, but manufacturing precision deteriorates resulting in non-linear touch traces
Solution Approach 1:
The patent changes the parameter of sensor signal processing by introducing differential calculation. Instead of directly using raw sensor signals for position determination, the system calculates differential values between adjacent sensors, which compensates for the non-linearity introduced by sparse sensor distribution. This parameter change allows the system to achieve linear touch traces while maintaining easy manufacturing of sparse sensor arrays
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 proposed solution effectively alleviates detection difficulties in close touches, reduces non-linearity in touch traces, and accurately detects inputs from pens held by fingers, improving the overall accuracy and reliability of position detection on touch panels.
Implementation Method 1
A self-capacitance detection may be performed by a sensing device
Implementation Method 2
a first mutual-capacitance detection may be performed for determining one or more first 1-D positions
Data Source
AI summary
A controller for position detection is disclosed. At least one first 1-D position corresponding to at least one external object is determined based on signals of a plurality of first sensors by self-capacitance detection. Then, at least one second 1-D position corresponding to the at least one first 1-D position is determined based on signals of a plurality of second sensors by mutual-capacitance detection, wherein each second 1-D position is determined based on a differential sensing information whose each value is based on signals of two second sensors by mutual-capacitance detection.