Capacitive Touch Filtering Using Walsh-Hadamard Sequency Bins
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Solution Overview
Problem
Conventional capacitive touch systems face challenges in reliably detecting touch events by gloved fingers and are often overly sensitive to bare hands or prone to false detections due to noise or contaminants, as they rely on raw capacitance thresholds that are not adequately sensitive to the smaller changes caused by gloved fingers.
Innovation Solution
Transforming raw capacitance signals from the time domain to the sequency domain using a Walsh-Hadamard transform allows for more accurate detection of touch events by evaluating signals in sequency bins, providing a better signal-to-noise ratio and enabling differentiation between touch and proximity events, even with gloved fingers, without requiring complex number processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If raw capacitance threshold detection is used, then the system is simple to operate, but it is overly sensitive to bare hands or prone to false detections
Solution Approach 1:
The patent transforms the detection parameter from raw capacitance values in the time domain to sequency domain coefficients through Walsh-Hadamard transform. This parameter transformation enables the system to distinguish between different types of capacitive events (touch vs. proximity) by analyzing the distribution of energy across different sequency bins, thereby improving detection reliability while maintaining operational simplicity
Solution Approach 2:
The patent introduces a new dimension of analysis by transforming the signal from time domain to sequency domain. This dimensional transformation allows the system to evaluate signals in terms of their sequency content rather than just temporal amplitude, providing additional discriminatory power for distinguishing touch events from proximity events without increasing operational complexity
2Speed
If raw capacitance threshold detection is used, then the system responds quickly to touch events, but it cannot differentiate between touch and proximity events
Solution Approach 1:
The patent segments the capacitive signal into different sequency components through Walsh-Hadamard transform, organizing the signal energy into distinct sequency bins. This segmentation allows the system to analyze different frequency characteristics of the capacitive event, enabling differentiation between touch and proximity events while maintaining fast response through efficient transform algorithms
Solution Approach 2:
The patent replaces traditional time-domain threshold comparison methods with a transform-based sequency domain analysis. This substitution enables more sophisticated event differentiation by examining the spectral characteristics of the capacitive signal, allowing the system to distinguish between touch and proximity events based on their different sequency signatures
3Reliability
If the system is tuned to detect gloved fingers, then it reduces false positives from bare hand proximity, but it becomes less sensitive to touch events
Solution Approach 1:
The patent employs feedback mechanisms where the sequency domain analysis provides information about the nature of the capacitive event. By analyzing the distribution of signal energy across different sequency bins, the system can adaptively distinguish between touch events (which produce characteristic sequency patterns) and proximity events (which produce different patterns), thereby reducing false positives while maintaining sensitivity to actual touches
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 enables reliable detection of touch events by gloved fingers and reduces false positives from noise or bare hand proximity, improving the system's sensitivity and specificity in capacitive sensing applications.
Implementation Method 1
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 or another reference potential
Implementation Method 2
This electric field establishes a capacitance, sometimes referred to as a parasitic capacitance, from the sensor electrode to ground or another reference potential
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.