Capacitance Sensor Signal Profiling for Liquid False Touch Rejection
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Solution Overview
Problem
Capacitive sensors in devices are prone to detecting false touches due to liquids and other capacitive objects, leading to unwanted device operations, and existing solutions increase power consumption and cost without effectively mitigating this issue.
Innovation Solution
A sensor array with a signal profile analysis method that sorts response signals by delta positions, forms an extended vector, and analyzes using a fitted curve to distinguish between touch events and false touches, employing techniques like mutual-cap and self-cap scanning to reject false inputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing solutions are used to mitigate false touches, then false touch detection is improved, but power consumption increases
Solution Approach 1:
The sensor array is divided into multiple independently scanable regions or groups, allowing selective scanning of only those areas where false touches are likely to occur, rather than scanning the entire array continuously. This segmentation enables power savings by activating only necessary sensor subsets while maintaining detection accuracy in critical areas.
Solution Approach 2:
The system dynamically adjusts scanning parameters such as scan frequency, threshold values, and analysis depth based on environmental conditions and operational context. During periods of low activity or when liquid presence is detected, the system reduces scanning intensity or skips unnecessary analysis steps, thereby lowering power consumption while maintaining reliable false touch detection when needed.
2Reliability
If existing solutions are used to mitigate false touches, then false touch detection is improved, but device cost increases
Solution Approach 1:
The system uses the existing sensor array infrastructure to perform self-diagnosis and false touch detection without requiring additional dedicated hardware components. By analyzing patterns in the signals already being captured by the capacitive sensors, the system achieves false touch mitigation using existing resources, thereby avoiding increased device cost while improving reliability.
Solution Approach 2:
The sensor array serves multiple functions: it detects genuine touches, identifies false touches from liquids, and provides environmental sensing capabilities. By making the existing sensor array multi-functional rather than adding separate dedicated sensors for false touch detection, the system improves reliability without proportionally increasing device complexity or cost.
3Measurement precision
If signal profile analysis is performed for every response signal, then touch detection accuracy is improved, but processing time increases
Solution Approach 1:
Instead of performing complete signal profile analysis on every response signal, the system applies partial analysis only when necessary. Quick threshold-based filtering is applied first to eliminate obviously invalid signals, and full profile analysis is reserved for borderline cases or when liquid presence is suspected. This selective approach maintains high detection accuracy while significantly reducing average processing time.
Solution Approach 2:
The system performs preliminary filtering and pre-analysis of response signals using simple criteria before committing to full signal profile analysis. By quickly identifying and discarding clearly invalid signals or grouping similar signals for batch processing, the system prepares data in advance to minimize the computational burden of detailed analysis, thereby reducing overall processing time while maintaining accuracy.
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
Effectively differentiates between genuine user interactions and false touches caused by liquids, reducing erroneous device responses and conserving power while maintaining low latency.
Implementation Method 1
An input element may include a capacitive sensor used to detect human touches and/or hover gestures
Data Source
AI summary
Techniques are provided for implementing liquid tolerance for a touch device. A sensor array of the touch device is scanned to generate response signals. In response to a response signal exceeding a touch threshold, a signal profile analysis is performed. The signal profile analysis includes sorting the response signals according to ascending order of delta positions to generate sorted signals. An extended vector of the sorted signals is formed. The extended vector of the sorted signals is analyzed using a fitted curve. In response to a feature of the fitted curve satisfying a criteria, the response signal is reported as a touch event. In response to the feature not satisfying the criteria, the response signal is rejected as a false touch.