Stylus Detection Noise Mitigation via Touch Data Modeling
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Solution Overview
Problem
Capacitive touch sensor panels face interference from noise sources, such as a display and conductive objects, which can hinder the accurate detection of an active stylus, leading to reduced performance and user experience.
Innovation Solution
The implementation of a touch sensor panel with noise mitigation techniques, where the electronic device models noise characteristics from touch data and stylus data to remove noise, improving the accuracy of stylus detection by determining noise profiles and scalar gains from proximate objects and display noise using predetermined functions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If noise mitigation techniques are implemented to improve stylus detection accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system performs preliminary noise characterization by identifying noise sources and modeling their characteristics before stylus detection. Touch data is collected and analyzed to create noise profiles that are then used to filter stylus signals, improving detection accuracy while managing complexity through structured preprocessing
Solution Approach 2:
The patent introduces an intermediary noise model that acts as a mediator between raw sensor data and stylus detection. The noise model characterizes interference from conductive objects and display elements, then removes this characterized noise from stylus signals, effectively decoupling the noise removal process from the core detection algorithm
2Reliability
If noise from conductive objects and display is removed from stylus data, then reliability is improved, but loss of information may occur
Solution Approach 1:
The noise removal process applies local quality control by characterizing noise properties at different locations and conditions. The system identifies specific noise sources (conductive objects, display elements) and applies targeted removal strategies tailored to each noise type and location, preserving genuine stylus signal variations while removing harmful interference
Solution Approach 2:
The system employs feedback mechanisms where touch data and stylus data are continuously analyzed to refine noise characterizations. The noise model is updated based on observed patterns, and removal parameters are adjusted in real-time to optimize the balance between noise reduction and signal preservation, preventing information loss
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 approach enhances the accuracy of stylus detection by effectively characterizing and removing noise, thereby improving the responsiveness and reliability of touch screen interactions.
Implementation Method 1
The active stylus can generate an electrical signal that the touch sensor panel or touch screen is able to detect to determine the location of the stylus
Data Source
AI summary
A touch screen or touch sensor panel can detect touches by conductive objects (e.g., fingers) and an active stylus and can mitigate noise in the sensed stylus signal from multiple noise sources. In some examples, the touch sensor panel includes a plurality of touch electrodes that can be used to sense touch data indicative of a proximate conductive object and to sense stylus data. The stylus data can include noise from one or more sources, for example. In some examples, the electronic device uses the touch data to determine a characteristic of one of the sources of noise and the stylus data to determine another characteristic of the source of noise and one or more characteristics of another source of noise. After modeling the noise, the electronic device can remove the noise from the stylus data to improve the accuracy of the stylus scan.