Capacitive Touch Signal Filtering Using Walsh-Hadamard Bins
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional capacitive touch systems face challenges in reliably detecting touch events by gloved fingers due to smaller changes in capacitance, often resulting in false negatives or false positives, especially when distinguishing between bare and gloved fingers, as well as being susceptible to noise and contaminants.
Innovation Solution
Transforming raw capacitance signals from the time domain to the sequency domain using a Walsh-Hadamard transform allows for improved signal processing, enabling better differentiation between touch and proximity events by evaluating transformed signals in sequency bins, which provides a more robust and sensitive method for detecting touch events, including those by gloved fingers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional capacitive touch systems use raw capacitance threshold comparison to detect touch events, then the system is simple to implement, but it produces false positives and false negatives when distinguishing between bare and gloved fingers
Solution Approach 1:
The patent replaces conventional time-domain capacitive signal analysis with a frequency-domain approach using Fast Fourier Transform (FFT). This substitution transforms the raw capacitance signal into frequency components, allowing the system to distinguish between different touch types (bare finger vs. gloved finger) by analyzing their distinct frequency signatures. The FFT-based method improves detection reliability by converting a simple threshold comparison into a sophisticated spectral analysis that can differentiate subtle capacitance variations.
2Measurement precision
If the system lowers the detection threshold to detect gloved fingers, then sensitivity to gloved touch improves, but false positives from noise and contaminants increase
Solution Approach 1:
The patent introduces frequency domain analysis as an intermediary layer between the raw capacitance signal and the touch detection decision. Instead of directly comparing raw capacitance values to thresholds, the system first transforms the signal into the frequency domain using FFT, then analyzes specific frequency bins (e.g., bins 1-3 for touch detection, bins 4-7 for noise identification). This intermediary transformation allows the system to identify genuine touch signals while filtering out noise and contaminants that appear as different frequency components.
3Measurement precision
If the system uses frequency domain analysis with FFT to improve touch detection, then the ability to distinguish between touch and proximity events improves, but computational complexity increases
Solution Approach 1:
The patent applies partial FFT analysis by focusing on specific frequency bins (bins 1-3 for touch detection, bins 4-7 for noise characterization) rather than analyzing the entire frequency spectrum. This selective approach to frequency domain analysis provides sufficient discrimination between touch and proximity events while reducing computational complexity compared to a full-spectrum analysis. The system processes only the relevant frequency components needed for accurate touch detection.
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 Walsh-Hadamard transform enhances the signal-to-noise ratio and improves the system's ability to accurately detect touch events, reducing false positives and negatives, and effectively differentiates between touch and proximity events, even in the presence of noise or contaminants.
Implementation Method 1
Transforming raw capacitance signals from the time domain to the sequency domain using a Walsh-Hadamard transform allows for improved signal processing
Implementation Method 2
The control circuit provides an excitation voltage to, and thereby generates an electric field about, the sensor electrode. This electric field establishes a capacitance, sometimes referred to as a parasitic capacitance, from the sensor electrode to ground
Implementation Method 3
Introduction of a stimulus, for example, a user's finger, to or near the sensor electrode or corresponding touch surface establishes an additional capacitance, sometimes referred to as a finger capacitance, from the electrode, through the finger, to ground, thereby changing the overall sensor electrode-to-ground capacitance
Data Source
AI summary
A transform is used to transform raw sensor data from the time domain to the frequency or sequency domain. The transformed data falls into several signal bins. The transformed data in at least one of the signal bins is analyzed to determine whether a touch event or release event has occurred.