Multi-touch Digitizer Palm Rejection via Temporal Tracking
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Solution Overview
Problem
Multi-touch digitizer systems face challenges in distinguishing between intended and unintended input, particularly from larger body parts like palms, hands, and arms, leading to erratic and false identification of input regions.
Innovation Solution
A method that tracks previous locations of palm input and invalidates output from regions recently identified as palm input, using a list of stored locations with time stamps to differentiate between intended and unintended input, thereby reducing false negatives and improving the robustness of palm rejection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional palm rejection methods are used to classify input regions, then some unintended palm input can be rejected, but the output becomes erratic and false identification of input regions occurs
Solution Approach 1:
The system performs preliminary classification of each input region as palm input or non-palm input at each refresh cycle before final processing. This preliminary action creates a history record that is used to stabilize subsequent classifications, preventing erratic output by anticipating potential false identifications based on previous cycle results.
Solution Approach 2:
The system uses feedback from previous refresh cycles to influence current classifications. By comparing current input region classifications with historical data from previous cycles, the system can identify and correct false identifications, thereby stabilizing the output while maintaining reliable palm rejection.
2Device complexity
If palm input regions are rejected based on current classification only, then processing is simple, but false negatives occur and intended input is incorrectly rejected
Solution Approach 1:
The system performs preliminary classification of each input region as palm input or non-palm input at each refresh cycle before final processing. This preliminary action creates a history record that is used to stabilize subsequent classifications, preventing erratic output by anticipating potential false identifications based on previous cycle results.
Solution Approach 2:
The system uses feedback from previous refresh cycles to influence current classifications. By comparing current input region classifications with historical data from previous cycles, the system can identify and correct false identifications, thereby stabilizing the output while maintaining reliable palm rejection.
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 enhances the stability of output by accurately invalidating unintended input from larger body parts, reducing erratic behavior and improving the accuracy of intended input detection, even when palm input is accompanied by intended fingertip input.
Implementation Method 1
a source of oscillating electrical energy at a predetermined frequency, and detection circuitry for detecting a capacitive influence on the sensing conductive line when the oscillating electrical energy is applied, the capacitive influence being interpreted as a touch
Data Source
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AI summary
A method for identifying intended input to a digitizer sensor includes identifying a plurality of regions of input to a digitizer sensor over a plurality of refresh cycles, classifying each of the plurality regions as one of intended input and unintended input, the classifying performed for each of the plurality of refresh cycles, storing a list of locations of regions classified as unintended input regions, where each entry of the list stored for a pre-defined time period and then subsequently removed from storage and invalidating output obtained from a region classified as a region of intended input, responsive to the region overlapping a location listed in the list of locations classified as unintended input regions.