Touch Sensing Driving Device Noise Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing touch driving devices struggle to accurately detect noise of varying intensity and type, particularly when noise intensity is low, making it difficult to distinguish from no-touch, power-on-palm, or Electrostatic Discharge (ESD) tests.
Innovation Solution
A sensing driving device and method that utilize a sensing circuit and processor to obtain raw data from a panel, calculate delta data using a baseline value, and categorize delta data into specific ranges to detect different types of noise. The processor determines the type of noise based on the range the delta data falls into, allowing for accurate noise detection and offsetting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If noise detection is performed using traditional methods, then large intensity noise can be detected easily, but small intensity noise cannot be distinguished from no-touch, power-on-palm, or ESD test signals
Solution Approach 1:
The patent segments the noise detection process into multiple ranges: a first range for large intensity noise, a second range for small intensity noise, and a third range for boundary cases. This segmentation allows the system to apply different detection strategies for different noise intensities, enabling precise detection of small intensity noise that would otherwise be indistinguishable from legitimate signals.
Solution Approach 2:
The patent applies local quality by treating different noise intensity levels differently. For small intensity noise in the second range, the system uses specialized detection criteria that distinguish it from no-touch, power-on-palm, and ESD test signals. This localized approach to quality control enables accurate detection across all noise intensity levels without false positives.
2Device complexity
If a single threshold is used for noise detection, then the detection process is simple, but it cannot accurately distinguish between different types of noise and signals
Solution Approach 1:
The patent divides the detection threshold into multiple ranges rather than using a single threshold. The first range handles large intensity noise, the second range handles small intensity noise, and the third range addresses boundary cases. This segmentation increases precision in noise type differentiation while maintaining reasonable process complexity through systematic classification.
Solution Approach 2:
The patent implements dynamic thresholding where the detection criteria adapt based on the measured noise intensity. The system dynamically selects which range applies to the current measurement, allowing for precise differentiation between noise types and signals. This dynamic approach balances complexity and precision by using a structured decision framework.
Data Source
AI summary
A sensing driving device includes a sensing circuit configured to obtain raw data from a panel; and a processor configured to obtain delta data from the raw data using a baseline value. The processor is configured to obtain whether the delta data is included in any one of a first range, a second range, and a third range, and detect different noises in accordance with the range in which the delta data is included. The first range is a range in which the delta data is located below the baseline value, the second range is a range in which the delta data is located between the baseline value and a touch-on threshold, and the third range is a range in which the delta data is located above the touch-on threshold. The touch-on threshold is greater than the baseline value.