Predictive Touch Surface Scanning for Capacitive Sensors
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Solution Overview
Problem
Existing touch-sensor technologies face challenges in efficiently tracking conductive objects with high accuracy and low power consumption, particularly in reducing noise immunity and response time while maintaining high refresh rates.
Innovation Solution
A capacitive touch-sensing system that limits the number of intersections scanned by predicting the location of a conductive object using previous locations, velocity, and acceleration, and performs local scans within a search window to accurately track the object, thereby reducing power consumption and improving noise immunity and response time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the entire sensor array is scanned at high refresh rates, then tracking accuracy is improved, but power consumption increases and noise immunity decreases
Solution Approach 1:
The sensor array is divided into multiple regions, and only a subset of intersections is scanned at any given time. The system segments the scanning process into multiple passes or zones, scanning only the relevant portions of the array at high refresh rates while reducing or skipping scans in other areas, thereby maintaining tracking accuracy for the conductive object while reducing overall power consumption.
Solution Approach 2:
Different regions of the sensor array are scanned with different frequencies or intensities based on their relevance. The system applies local quality by focusing scanning resources on areas where conductive objects are likely to appear or move, while reducing scanning activity in less critical regions, thus maintaining high tracking accuracy where needed while reducing power consumption overall.
2Measurement precision
If the entire sensor array is scanned at high refresh rates, then tracking accuracy is improved, but noise immunity deteriorates
Solution Approach 1:
The scanning process is segmented to scan only specific intersections or regions at high refresh rates, reducing the total number of scans performed. This segmentation reduces the accumulation of noise from unnecessary scans while maintaining accurate tracking by focusing on the most relevant sensor intersections, thereby improving noise immunity without sacrificing tracking accuracy.
3Loss of time
If predictive scanning is implemented, then response time is reduced, but measurement precision may deteriorate
Solution Approach 1:
The system performs preliminary actions by predicting the likely location of conductive objects based on previous positions and motion patterns. This prediction allows the system to pre-identify which intersections are most likely to contain the conductive object and scan those first, reducing response time by avoiding unnecessary scans in unlikely areas while maintaining precision by focusing on predicted locations.
Solution Approach 2:
The system uses feedback from previous scan results and conductive object positions to refine future scanning predictions. By continuously learning from past data about object movement patterns, the system improves the accuracy of its predictions, thereby reducing response time while maintaining or enhancing measurement precision through adaptive, feedback-driven scanning decisions.
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 system achieves improved accuracy, reduced response time, and increased noise immunity by limiting scanned intersections, resulting in enhanced performance and power efficiency in tracking conductive objects on touch-sensing surfaces.
Implementation Method 1
A capacitive touch-sensing surface may be used to track locations of one or more conductive objects in contact or in close proximity to the touch-sensing surface by scanning each of a number of intersections between capacitive sensor elements
Data Source
AI summary
A method for locating a conductive object at a touch-sensing surface may include detecting a first resolved location for the conductive object at the touch-sensing surface based on a first scan of the touch-sensing surface, predicting a location for the conductive object, and determining a second resolved location for the conductive object by performing a second scan of a subset of sensor elements of the touch-sensing surface, wherein the subset of sensor elements is selected based on the predicted location of the conductive object.