Model-Based Touch Event Location Adjustment for Mobile Devices
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Solution Overview
Problem
Mobile devices with small touchscreens face challenges in precise touch sensing due to user motion and orientation variance, leading to inaccuracies in touch detection and user experience.
Innovation Solution
Implementing a model-based touch event location adjustment system that uses contextual sensors and machine-learned models, such as regression trees, to correct for motion and orientation effects, allowing for less precise touch sensing components and reducing manufacturing costs and power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-precision touch sensing components are used, then touch sensing accuracy is improved, but manufacturing cost and power consumption increase
Solution Approach 1:
A computational model acts as an intermediary between the touch sensor and the user interface system. The model receives raw touch data from less precise sensors and computationally adjusts the touch event location to compensate for motion and orientation effects, achieving accurate touch detection without requiring expensive high-precision hardware
Solution Approach 2:
The patent replaces mechanical precision requirements with computational processing. Instead of relying on mechanically precise touch sensors, the system uses software-based motion models and regression algorithms to achieve accurate touch event location determination through mathematical computation rather than hardware precision
2Measurement precision
If high-precision touch sensing components are used, then touch sensing accuracy is improved, but power consumption increases
Solution Approach 1:
A computational model serves as an intermediary that processes touch data from low-power, less precise sensors. The model compensates for motion effects through calculation rather than requiring continuous high-precision sensing, thereby reducing overall power consumption while maintaining accurate touch detection
Solution Approach 2:
The system changes the operational parameters of touch sensing by using less precise but lower-power sensors in combination with computational correction. The model dynamically adjusts touch event location based on motion parameters from other sensors, achieving accurate results with lower energy consumption than continuous high-precision sensing would require
3Measurement precision
If model-based touch event location adjustment is implemented, then touch sensing accuracy is improved, but device complexity increases
Solution Approach 1:
The touch processing system is segmented into distinct functional components: raw touch data acquisition, motion data acquisition from separate sensors, computational model processing, and final touch event generation. This modular segmentation allows each component to be optimized independently and simplifies the overall system architecture despite the added computational layer
Data Source
AI summary
An electronic device includes a display including a touch sensor, a contextual sensor configured to provide data indicative of an operating condition of the electronic device, one or more memories in which touch input instructions, touch event mapping instructions, and a touch event mapping model are stored, and a processor coupled to the memory. The processor is configured through execution of the touch input instructions to obtain data indicative of an initial assessment of touch event position via the touch sensor. The touch event mapping model maps the initial assessment of touch event position to an adjusted touch event position as a function of the data indicative of the operating condition of the electronic device. The processor is further configured through execution of the touch event mapping instructions to determine the adjusted touch event position based on the touch event mapping model, the data indicative of the initial assessment of touch event position, and the data indicative of the operating condition.