Touch Gesture Sensing with Vibration and Charge Cross-Validation
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Solution Overview
Problem
Existing touch gesture detection systems in mobile devices face issues with mechanical button fragility, unreliable capacitive sensors due to environmental electrical charge, and high energy consumption, leading to false positives and incompatibility with certain devices.
Innovation Solution
A system utilizing a processing unit coupled with an accelerometer and an electrostatic charge variation sensor to detect touch gestures by filtering vibration signals through a high-pass filter, identifying peaks and stationarity conditions, and validating touch events based on predefined thresholds and variance analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If mechanical buttons are used for touch gesture detection, then the device structure is simple and reliable, but the mechanical components are subject to breakage due to structural weakness and water resistance problems
Solution Approach 1:
The patent replaces mechanical buttons with a capacitive sensor system that detects touch gestures through electrical field changes. The processing unit analyzes capacitance variations at different locations to identify gesture patterns, eliminating mechanical components entirely while maintaining gesture detection functionality.
Solution Approach 2:
The patent introduces a processing unit as an intermediary that analyzes capacitance signals and distinguishes between intentional user gestures and environmental disturbances. By processing the electrical signals through algorithms that recognize gesture patterns, the system filters out false positives from environmental electrical charge while responding to deliberate user input.
2Adaptability or versatility
If capacitive sensors are used for touch gesture detection, then the device achieves full-screen coverage and eliminates mechanical parts, but the sensors are subject to disturbances from environmental electrical charge causing false positives
Solution Approach 1:
The patent segments the capacitive sensor surface into multiple detection zones with different capacitance thresholds. By dividing the full-screen surface into regions and analyzing capacitance changes in each segment, the system can distinguish between environmental disturbances (which typically affect large areas uniformly) and intentional gestures (which affect specific localized regions with characteristic patterns).
Solution Approach 2:
The processing unit implements feedback analysis by continuously monitoring capacitance variations and comparing them against learned gesture patterns. The system analyzes the temporal and spatial characteristics of capacitance changes, using feedback from previous detections to refine gesture recognition and filter out environmental noise that does not match characteristic gesture patterns.
3Speed
If traditional touch detection methods are used, then the system responds quickly to user input, but the energy consumption is high due to continuous sensor activation and processing
Solution Approach 1:
The patent implements periodic sampling of capacitance values at the sensor surface rather than continuous monitoring. The processing unit activates the sensors and performs gesture analysis at specific intervals, reducing energy consumption while maintaining responsive gesture detection. The periodic activation allows the system to remain in a low-power state between sampling cycles.
Solution Approach 2:
The system performs partial processing by initially analyzing only the most significant capacitance changes that exceed a threshold, reserving more intensive processing for confirmed gesture patterns. This approach reduces the average energy consumption by avoiding full gesture analysis for every sensor activation, while still maintaining quick response for actual gestures.
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
This approach reduces false positives, lowers energy consumption, and expands gesture recognition capabilities, making it suitable for various devices while maintaining high accuracy.
Implementation Method 1
an accelerometer, operatively coupled to the processing unit, configured to detect a vibration at said detection surface and generate a corresponding vibration signal
Implementation Method 2
an electrostatic charge variation sensor, operatively coupled to the processing unit, configured to detect an electrostatic charge variation at said detection surface and, as a result, generate a charge variation signal
Data Source
AI summary
System for detecting a touch gesture of a user on a detection surface, comprising: a processing unit; and an accelerometer to detect a vibration at the detection surface and generate a vibration signal. The processing unit is configured to: acquire the vibration signal, detect, in the vibration signal, a signal characteristic which can be correlated to the touch gesture of the user, detect, in the vibration signal, a stationarity condition preceding and/or following the detected signal characteristic, and validate the touch gesture in the event that both the signal characteristic and the stationarity condition have been detected. An electrostatic charge sensor may also be used as a further parameter to validate the touch gesture.