Touchscreen Signal Processing With Partial Sampling and Touch Refinement
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Solution Overview
Problem
Touchscreen panels face challenges in reducing power consumption while maintaining detection accuracy and responsivity, as current methods either increase noise signals or require higher excitation voltages, leading to increased power consumption and reduced detection accuracy.
Innovation Solution
The method involves reducing the number of sampled sensor areas by selecting a subset based on a sampling fraction, using compressive sensing and spatial low-pass filtering to improve detection accuracy and reduce noise, and dynamically adjusting the sampling pattern based on touch event detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If the number of sampled sensor areas is reduced, then power consumption decreases and responsivity improves, but detection accuracy deteriorates and noise signals increase
Solution Approach 1:
The sensor array is divided into multiple zones or regions, and only certain zones are sampled at full resolution while others are sampled at reduced resolution or skipped entirely. This segmentation allows the system to focus computational resources on areas where touch events are most likely to occur, maintaining detection accuracy in critical regions while reducing overall power consumption.
Solution Approach 2:
Instead of sampling all sensor areas at full resolution, the system applies partial sampling by selecting a subset of sensor areas based on a sampling fraction. This partial action reduces the number of measurements taken, thereby decreasing power consumption and improving responsivity while maintaining sufficient detection accuracy through intelligent selection of which areas to sample.
2Productivity
If the number of sampled sensor areas is reduced, then the acquisition speed increases, but the resolution and detection accuracy decrease
Solution Approach 1:
The sensor array is divided into multiple zones or regions, and only certain zones are sampled at full resolution while others are sampled at reduced resolution or skipped entirely. This segmentation allows the system to focus computational resources on areas where touch events are most likely to occur, maintaining detection accuracy in critical regions while reducing overall power consumption.
Solution Approach 2:
Instead of sampling all sensor areas at full resolution, the system applies partial sampling by selecting a subset of sensor areas based on a sampling fraction. This partial action reduces the number of measurements taken, thereby decreasing power consumption and improving responsivity while maintaining sufficient detection accuracy through intelligent selection of which areas to sample.
3Measurement precision
If excitation voltages are increased to overcome noise signals, then detection accuracy improves, but power consumption increases
Solution Approach 1:
The system extracts and removes offset values and noise signals from the measured sensor data through signal processing techniques. By subtracting reference offset values and applying filtering operations, the system recovers the actual touch signal from the noisy measurements, maintaining detection accuracy without requiring higher excitation voltages and thus avoiding increased power consumption.
Solution Approach 2:
Signal processing operations serve as an intermediary between the raw sensor measurements and the final touch detection. By introducing intermediate processing steps such as offset subtraction, filtering, and signal enhancement, the system improves detection accuracy without directly increasing the excitation voltage, thereby avoiding the associated power consumption increase.
Data Source
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Figure 3~4A
AI summary
A method includes obtaining a partial frame by sampling parts of a frame from a touch panel which comprises an array of sensor areas (step S1). The method also includes generating, based on the partial frame, a new frame which comprises estimates of the un-sampled parts (step S2). The method also includes determining whether at least one touch event is present in the new frame (step S3), and upon a positive determination, for each touch event, determining a location of the touch event in the new frame and obtaining a sub-frame by sampling a region of a subsequent frame from the touch panel frame at and around the location (step S4). The method also includes outputting touch information based on one or more sub-frames (step S7).