Touch Contact Tracking Using Predicted Location Shifting
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Solution Overview
Problem
Touch screens experience jittering in detected location due to noise interference, causing inaccuracies in tracking external conductive objects.
Innovation Solution
A prediction-based touch contact tracking method that generates predicted locations by shifting detected locations backwards and using a vector multiplication factor between 1 and 1.5 to reduce noise-induced jittering, employing filtering and interpolation techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detected locations are used directly from touch screen signals, then the reported locations reflect real-time touch positions, but jittering occurs due to noise interference
Solution Approach 1:
The system performs prediction of future touch locations in advance before the actual touch occurs. By calculating predicted locations based on historical touch data and motion patterns, the system prepares compensated location values proactively, reducing the impact of noise when the actual touch is detected.
Solution Approach 2:
The system continuously compares predicted locations with actual detected locations and uses this feedback to adjust the prediction model. The difference between predicted and actual locations is used to refine the prediction algorithm, improving its ability to filter noise while maintaining accuracy over time.
2Reliability
If noise filtering is applied to reduce jittering, then location stability improves, but response time increases due to processing delays
Solution Approach 1:
Location prediction is performed in advance based on historical touch patterns and motion vectors. By pre-calculating where the touch is likely to be next, the system reduces the need for complex real-time filtering operations, thereby maintaining location stability without significant processing delays.
Solution Approach 2:
The prediction algorithm dynamically adjusts its parameters based on the detected motion patterns and velocity of the touching object. When motion is rapid, the prediction adapts to reduce processing iterations; when motion is slow, more precise filtering can be applied, optimizing the balance between stability and response time.
Data Source
AI summary
When an external object approaches or touches a touch sensor, predicted locations of the external object can be generated by detected locations according to signals from the touch sensor. The latest predicted location is shifted backwards towards the latest reported location for a portion of the distance between the predicted location and the latest reported location to generate a new reported location, whereby jittering of the reported locations caused by noise in the signals of the touch sensor can be reduced or filtered.