3D Data Imaging Drive Sense Circuit Dynamic Compression
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Solution Overview
Problem
Existing data compression techniques for three-dimensional data, such as those generated by touch screens and 3D imaging sensors, often fail to balance data reduction with preservation of the intended use of the data, leading to inefficiencies in data transmission and processing.
Innovation Solution
Employing a combination of data reduction schemes, including lossy and lossless methods like Principal Component Analysis (PCA), contour mapping, and filtering, to selectively reduce capacitive grid data based on the intended use, such as touch detection, hover recognition, or pattern recognition, while maintaining data integrity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data compression techniques are applied to reduce data transmission, then data transmission efficiency is improved, but data accuracy and integrity deteriorate
Solution Approach 1:
The patent applies dynamic data reduction by adjusting the level of compression based on the specific use case. For touch detection, minimal reduction is applied to preserve accuracy, while for hover recognition or pattern identification, more aggressive reduction is acceptable. This dynamic approach allows the system to optimize transmission efficiency while maintaining data accuracy where critical.
Solution Approach 2:
The patent implements selective data reduction where different portions of the capacitive grid data are processed differently based on their importance. Critical touch detection regions maintain full precision, while less critical areas undergo more aggressive compression. This local differentiation resolves the contradiction by preserving accuracy where needed while improving overall transmission efficiency.
2Measurement precision
If full capacitive grid data is transmitted, then data accuracy is maintained, but data transmission rate and processing requirements increase
Solution Approach 1:
The patent extracts and transmits only the essential information from the full capacitive grid data. By identifying and removing redundant data elements that do not contribute to the intended use (touch detection, hover recognition, pattern identification), the system maintains data accuracy for critical functions while significantly reducing transmission rate and processing requirements.
Solution Approach 2:
The patent applies partial data transmission by sending only the necessary portion of the capacitive grid data rather than the complete dataset. This partial action approach maintains sufficient accuracy for the intended applications while reducing overall data transmission volume and processing burden.
3Device complexity
If data reduction is applied to optimize transmission, then data processing requirements are reduced, but data integrity for intended use deteriorates
Solution Approach 1:
The patent employs dynamic data reduction strategies that adapt to the specific intended use. For applications requiring high data integrity like touch detection, minimal reduction is applied. For applications where some integrity loss is acceptable like hover recognition or pattern identification, more aggressive reduction optimizes processing requirements. This dynamic adaptation resolves the contradiction between processing efficiency and data integrity.
Solution Approach 2:
The patent changes the parameters of data reduction based on the intended application. By adjusting compression levels, selection criteria, and processing intensity according to the specific use case, the system optimizes the balance between reducing processing requirements and maintaining sufficient data integrity for each application scenario.
Data Source
AI summary
A method includes, for a first x-y position of a sensing grid, obtaining first sensed data. The method further includes, for a first sense data layer, determining whether the first sensed data compares favorably to a threshold for the first sense data layer. The method further includes, when the first sensed data compares favorably to the threshold for the first sense data layer; storing a first n-bit value and storing a second n-bit value when it does not. The method further includes, for a second sense data layer, determining whether the first sensed data compares favorably to a threshold for the second sense data layer. The method further includes, when the first sensed data compares favorably to the threshold for the second sense data layer; storing the first n-bit value and storing the second n-bit value when it does not. The method includes similar processing for a second x-y position.