Capacitive Touch Sensor Signal Processing for Noise Immunity

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Solution Overview

Problem

Capacitive touch sensors face challenges in enhancing the signal-to-noise ratio (SNR) due to noise interference from sources like liquid crystal displays and other environmental factors, which affects the accuracy of touch position detection and can lead to false touches.

Innovation Solution

The implementation of digital signal processing techniques, including the use of orthogonal excitation waveforms, correlation signal compensation, and adaptive noise rejection methods, along with optimized scanning strategies and analog front-end circuit designs, to improve the SNR and reduce noise interference.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If capacitive touch sensors are used in noisy environments (e.g., with liquid crystal displays), then the sensor can provide touch detection functionality, but noise interference reduces the signal-to-noise ratio and causes false touches

Engineering Contradiction:

Improvetouch detection accuracyVSAvoidnoise interference

Core Design Contradiction:

ReliabilityVSObject-affected harmful factors

Solution Approach 1:

The touch sensor surface is divided into multiple independent sensing regions or zones, allowing the system to process and analyze signals from different segments separately. This segmentation enables localized noise filtering and improves overall detection reliability by isolating affected regions from unaffected ones.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system dynamically adjusts sensing parameters such as integration time, threshold levels, and signal filtering characteristics based on detected noise conditions. By changing these parameters in response to environmental conditions, the sensor maintains optimal performance across varying noise levels while reducing false touches.

Inventive Principle:

Principle #35Parameter changes

2Measurement precision

If signal processing techniques are applied to improve SNR, then touch detection accuracy improves, but processing time and computational complexity increase

Engineering Contradiction:

Improvetouch position detection accuracyVSAvoidsignal processing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs preliminary calibration and characterizes noise patterns during manufacturing or initial operation, storing reference data for later use. This preliminary action allows the sensor to apply pre-computed correction factors and noise profiles during actual touch detection, significantly reducing real-time processing requirements while maintaining high measurement precision.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system creates and stores reference signal models and noise profiles during calibration phases. These copied reference patterns are then used for comparison and validation during operational touch detection, enabling fast pattern matching algorithms that achieve high precision without requiring complex real-time computations.

Inventive Principle:

Principle #26Copying

Data Source

PatentUS10126889B2Techniques for locally improving signal to noise in a capacitive touch sensor

Publication Date: 2018.11.13 MICROSOFT TECHNOLOGY LICENSING LLC

AI summary

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for digital signal processing (DSP) techniques for generally improving a signal-to-noise ratio (SNR) of capacitive touch sensors.