Touch Input Anchor Classification for Vehicle Precision
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Solution Overview
Problem
Touch-sensitive devices, such as touchscreens and trackpads, often misinterpret 'anchor' contacts as user inputs, leading to decreased precision and frustration, especially in vehicles where users must extend their arms to reach the input area and are affected by vehicle movement.
Innovation Solution
A method and system to classify detected contacts as anchors or user inputs by analyzing contact characteristics, such as shape, duration, and location, using sensor data like accelerometer and pressure sensors, to distinguish between intended inputs and anchoring actions, thereby preventing misinterpretation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users create an anchor by resting part of their hand on the touch-sensitive device to steady their hand, then touch input precision is improved, but the anchor contact may be incorrectly interpreted as a user input, causing frustration
Solution Approach 1:
The system segments touch contacts into different categories (anchor contacts vs. intentional input contacts) by analyzing multiple characteristics simultaneously. This segmentation allows the system to distinguish between stabilizing touches and intentional inputs, resolving the contradiction between needing anchors for precision and avoiding false input detection.
Solution Approach 2:
The system dynamically adjusts its interpretation of touch contacts based on real-time analysis of contact characteristics such as duration, pressure, location, and movement patterns. This dynamic classification enables the system to adapt to different user behaviors and contexts, improving both precision and reliability.
2Ease of operation
If users extend their arm to reach the touchscreen in vehicles, then accessibility is improved, but touch precision decreases due to greater extension distance
Solution Approach 1:
The system introduces an intermediary classification layer that analyzes touch characteristics before processing inputs. This intermediary analysis acts as a mediator between the user's extended-arm touches and the system's input interpretation, compensating for the precision loss due to arm extension by intelligently distinguishing intentional inputs from accidental touches.
3Speed
If the touch-sensitive device processes all detected contacts as user inputs, then responsiveness is improved, but false inputs from anchors cause errors
Solution Approach 1:
The system performs preliminary classification of touch contacts based on their characteristics (duration, pressure, location, movement) before processing them as inputs. This preliminary action filters out anchor contacts that are unlikely to be intentional inputs, maintaining responsiveness to genuine user actions while preventing false input processing.
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 improves the accuracy of user input detection by filtering out anchor contacts, enhancing the precision of user interactions, particularly in challenging environments like vehicles, where users need to stabilize their hands while making inputs.
Implementation Method 1
analyzing contact characteristics, such as shape, duration, and location, using sensor data like accelerometer and pressure sensors
Implementation Method 2
analyzing variations in the contact over time, determining an anchor confidence score based on the analysis
Data Source
AI summary
Methods, systems, and apparatus for receiving data corresponding to a contact by a user detected at a touch-sensitive device. Variations in the contact over time are analyzed, and an anchor confidence score that is indicative of whether the contact represents a user input made using the touch-sensitive device is determined based at least on the analysis of the variations in the contact over time. The contact is classified as an anchor based at least on the anchor confidence score. Based on classifying the contact as an anchor, the contact is not processed as a user input to the touch-sensitive device.