Touch Error Calibration via Adaptive Location Mapping
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Solution Overview
Problem
Users experience frustration and decreased user experience due to touch input errors on virtual keyboards, where finger size and shape variations lead to incorrect letter recognition, especially when using portable devices like smartphones and tablets, resulting in inconvenience and potential device rejection.
Innovation Solution
A system and method for calibrating touch errors by recognizing objects on a touch interface, determining the intended target object, and automatically adjusting the touch recognition based on collected location information, including dividing the keyboard into sections for right-handed and left-handed users to improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a virtual touch keyboard is used on portable devices, then device portability and ease of carrying are improved, but touch input accuracy deteriorates due to finger size and shape variations
Solution Approach 1:
The system dynamically adjusts touch recognition parameters by collecting location information from multiple touches of the same target object and calculating correction values. These correction values modify the touch recognition parameters to compensate for individual finger characteristics, thereby maintaining touch input accuracy while preserving the portability benefits of virtual keyboards.
Solution Approach 2:
The system implements a feedback mechanism where touch errors are detected, correction information is generated based on the difference between touched and intended objects, and this correction information is stored and applied to future touch recognitions. This continuous feedback loop progressively improves touch input accuracy for each user based on their specific finger characteristics.
2Measurement precision
If touch error calibration is performed by collecting location information for multiple objects, then touch input accuracy is improved, but system complexity increases
Solution Approach 1:
The calibration process is segmented into distinct functional modules: an object recognizing unit that identifies touched objects, a target object determining unit that identifies intended objects, a storing control unit that manages location information, and a calibrating unit that applies corrections. This modular segmentation reduces system complexity by organizing the calibration functionality into manageable, independent components.
Solution Approach 2:
The system performs self-calibration by automatically collecting touch location information, generating correction values, and applying them without requiring external intervention or manual configuration. The system serves itself by learning from user touch patterns and autonomously improving touch recognition accuracy, thereby reducing the operational complexity for users.
3Measurement precision
If the touch keyboard is divided into sections for right-handed and left-handed users, then touch recognition accuracy for specific users is improved, but device complexity increases
Solution Approach 1:
The touch keyboard is divided into different sections with locally optimized correction values for right-handed and left-handed users. Each section has tailored calibration parameters that account for the different touch patterns and finger positions characteristic of each user group. This local quality approach improves touch recognition accuracy for specific users while maintaining a unified keyboard layout, avoiding the need for completely separate devices.
Data Source
AI summary
A system for calibrating touch error in a touch interface includes an object recognizing unit to recognize at least one object input through a touch interface from a plurality of objects on a touch keyboard; a target object determining unit to determine whether the recognized object corresponds to a target object that a user intended to input; a storing control unit to match and store location information corresponding to the recognized object and at least one location information corresponding to the target object; and a calibrating unit to calibrate the recognized object input through the touch interface to the target object based on the matched and stored location information. Methods for calibrating touch error are also disclosed.