Adaptive Gesture Recognition for Touch Input
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Solution Overview
Problem
Existing user interfaces, such as touch screens and directional pads, often struggle to recognize gestural inputs accurately, leading to user frustration due to imperfect movements and restrictive recognition parameters that fail to accommodate individual user variations.
Innovation Solution
Adaptive gesture recognition systems that adjust recognition parameters based on actual user behaviors, allowing for the recognition of gestures that do not initially meet predefined criteria by considering additional factors and storing adapted parameters for future use.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If strict gesture recognition parameters are used to ensure accurate gesture identification, then measurement precision is improved, but ease of operation deteriorates due to user frustration from imperfect movements not being recognized
Solution Approach 1:
The system dynamically adapts gesture recognition parameters based on individual user behavior patterns. Instead of using fixed strict parameters, the system learns and adjusts parameters such as movement thresholds, timing windows, and gesture boundaries to match each user's natural interaction style, thereby maintaining recognition accuracy while accommodating variations in user movement quality
Solution Approach 2:
The system changes recognition parameters adaptively based on observed user behavior. By monitoring successful and unsuccessful gesture attempts, the system modifies parameters like sensitivity thresholds, gesture duration ranges, and movement velocity expectations to better align with individual user capabilities, resolving the conflict between strict recognition and user-friendly operation
2Measurement precision
If restrictive gesture parameters are applied to maintain consistent recognition standards, then measurement precision is improved, but adaptability deteriorates as the system cannot accommodate variations between different users
Solution Approach 1:
The system performs preliminary learning during an onboarding phase or initial usage period to establish baseline gesture patterns for each user. This preliminary action captures user-specific movement characteristics before full system operation begins, enabling the system to maintain consistent recognition standards while being pre-adapted to individual user variations
Solution Approach 2:
The system implements continuous feedback loops where unrecognized or partially recognized gestures are analyzed to refine user-specific parameter sets. This feedback mechanism allows the system to maintain overall recognition consistency across the user base while adapting to individual variations through iterative parameter adjustment based on actual usage data
Data Source
AI summary
Systems and methods are described for adaptively recognizing gestures indicated by user inputs received from a touchpad, touchscreen, directional pad, mouse or other multi-directional input device. If a user's movement does not indicate a gesture using current gesture recognition parameters, additional processing can be performed to recognize the gesture using other factors. The gesture recognition parameters can then be adapted so that subsequent user inputs that are similar to the previously-rejected inputs will appropriately trigger gesture commands as desired by the user. Gestural data or parameters may be locally or remotely stored for further processing.