Trace Input Compensation Using Accelerometer Data
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Solution Overview
Problem
Existing user interfaces struggle to accurately interpret trace inputs on surfaces, especially when the surface experiences movement, leading to errors in handwriting recognition and other input recognition tasks due to motion-induced variability.
Innovation Solution
A processor-configured system that receives trace inputs on a surface and compensates them based on movement data from sensors like accelerometers, adjusting the inputs to counterbalance the effects of surface movement and improve recognition accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If trace input is entered on a moving surface, then input can be captured, but recognition accuracy deteriorates due to motion-induced variability
Solution Approach 1:
The system uses motion sensors to detect surface movement and feeds this information back to the processor, which then compensates the trace input coordinates based on the detected motion, resolving the accuracy deterioration caused by surface movement
Solution Approach 2:
The system changes the coordinate system parameters by applying motion compensation transformations to the trace input data, adjusting the coordinates to account for surface movement and maintain recognition accuracy
2Measurement precision
If motion compensation is applied to trace input, then recognition accuracy is improved, but device complexity increases due to additional sensors and processing
Solution Approach 1:
The motion sensor serves multiple functions: detecting surface movement for compensation purposes and potentially other motion-related functions, reducing the need for separate dedicated components and mitigating complexity increase
Solution Approach 2:
The processor acts as an intermediary that receives both trace input data and motion sensor data, performing coordinate transformation and compensation to bridge the gap between raw input and recognized output, simplifying the overall system architecture
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
Enhances the accuracy of handwriting and gesture recognition by dynamically correcting trace inputs in real-time, reducing the need for re-entry in shaky environments and improving overall input recognition precision.
Implementation Method 1
a movement sensor that is configured to detect movement of the surface from a first position to a second position
Data Source
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Figure 2
Figure 3a~3d
AI summary
User input data and movement data relating to movement of a device to which the user input is made is monitored. The input data may be modified according to the movement data so that inadvertent inputs based on an unwanted tremors, bumps, or similar are accounted for. Data from an accelerometer may indicate sudden movement or bumps. The input data, such as handwriting for example, may then be modified based on the data from the accelerometer. Therefore, the device may determine the input as intended by the user.