Bump Suppression via Multi-Sensor Fusion Filtering
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Solution Overview
Problem
Existing gesture-based input systems for electronic devices often misinterpret user inputs due to the sensitivity of accelerometers, leading to confusion between intended gestures like bumps, tilts, and screen touches, resulting in decreased application utility.
Innovation Solution
Implementing a filtering system that combines data from multiple physical sensors, such as accelerometers, touch sensors, and microphones, using timing relationships and other sensor data to differentiate between intentional and unintentional gestures, thereby improving the reliability of bump-based inputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If accelerometer sensitivity is increased to detect bumps, then bump detection capability is improved, but false detection of unintended movements increases
Solution Approach 1:
The patent combines data from multiple sensors (accelerometer, gyroscope, magnetometer, touch sensor, microphone) to differentiate between intended bumps and unintended movements. By merging sensor inputs and analyzing their temporal relationships, the system achieves reliable bump detection without false positives from accidental movements or screen touches.
Solution Approach 2:
The system uses feedback from multiple sensor channels to validate accelerometer-derived bump events. Touch sensor feedback confirms whether the device was held still, gyroscope feedback verifies absence of unintended movements, and microphone feedback detects bump sounds. This multi-channel feedback mechanism filters false positives while maintaining sensitivity.
2Reliability
If multiple sensors are combined to filter gesture input, then input reliability is improved, but device complexity increases
Solution Approach 1:
The filtering system is segmented into distinct functional modules: accelerometer event detection, touch sensor validation, gyroscope movement detection, microphone sound detection, and temporal relationship analysis. Each module processes specific sensor data independently, then results are combined to make final bump determination. This modular segmentation manages complexity while maintaining high reliability.
Data Source
AI summary
Apparatus and methods for reducing misinterpretation of gesture-based input to portable electronic devices are described.