Touchless Screen Finger Detection via Capacitance Macro-Area Analysis
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Solution Overview
Problem
Current touch screens and touchless devices face security vulnerabilities as they can reconstruct passwords from finger traces on the screen and movement data from sensors, compromising user privacy and security, especially in applications requiring sensitive operations like online financial transactions and confidential communications.
Innovation Solution
A method using projected capacitive technology with self-sensing mode to detect a finger hovering over the screen by generating detection signals in the X and Y directions, sampling these signals to create raw-data vectors, dividing them into macro-areas, computing cumulative values, and identifying the macro-area of the finger's position without direct contact, thereby preventing password reconstruction and enhancing security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If touch screen technology is used for password entry, then ease of operation is improved, but security deteriorates due to finger trace reconstruction
Solution Approach 1:
The patent replaces the mechanical touch interaction system with an optical sensing system. Instead of detecting physical finger contact through mechanical sensors, the system uses optical sensors to detect reflected light patterns caused by finger proximity, eliminating direct mechanical contact and thus preventing finger trace formation while maintaining operational capability.
Solution Approach 2:
The patent introduces light as an intermediary medium between the user's finger and the password entry system. The optical sensor detects changes in light reflection patterns caused by the finger's proximity, using this intermediary signal to determine password input without requiring direct mechanical contact, thereby preventing trace reconstruction.
2Measurement precision
If accelerometer sensors are used to detect movement, then measurement precision is improved, but security deteriorates due to password reconstruction capability
Solution Approach 1:
The patent extracts and removes the accelerometer sensor from the system entirely. Instead of using movement sensors that can track finger trajectory and potentially reconstruct passwords, the system uses only optical sensors to detect the presence and position of the finger through light reflection, eliminating the harmful component while preserving the useful function of detecting user input.
Solution Approach 2:
The patent converts the potentially harmful light reflection from the finger into a beneficial detection signal. Instead of using accelerometers that could track movement patterns, the system uses the optical reflection properties of the finger to create a secure detection mechanism that prevents password reconstruction while maintaining measurement capability.
3Reliability
If touchless screen technology is used, then security is improved by preventing finger marks, but device complexity increases
Solution Approach 1:
The patent makes the optical sensor system multi-functional by using the same optical detection mechanism for both password entry detection and security verification. The system uses the optical sensor to detect finger proximity for password input, and the same sensor detects the absence of finger contact to prevent unauthorized access, eliminating the need for separate security mechanisms and reducing overall system complexity.
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 solution ensures secure password entry by not leaving finger marks on the screen and not using accelerometer data, effectively preventing unauthorized password reconstruction, thus enhancing the security of touchless devices.
Implementation Method 1
a screen of a touchless type, which exploits a projected capacitive technology... the controller reads the variation of capacitance at the intersection of each row and column of the virtual grid
Data Source
AI summary
Detecting the presence of a finger in proximity of a screen that generates detection signals in the horizontal direction and vertical direction includes sampling the detection signals and generating raw-data vectors X and Y. The raw data have a maximum for elements of the vector that define the position of the finger on the screen in the directions X and Y, respectively. The vectors X and Y are divided into subsets defined as “macro-areas” and cumulative values computed of each macro-area by adding together all the elements of the vector X and of the vector Y that belong to the macro-area. The maximum values are selected from among horizontal cumulative values and vertical cumulative values. A value identifying the macro-area selected on the basis of the maximum values is supplied, or no value supplied in the presence of elements of disturbance in the proximity of the screen.