Event-Based Sensor Flickering Noise Filtering
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Solution Overview
Problem
Existing sensors face challenges in distinguishing between meaningful and meaningless events, leading to unnecessary resource consumption and power wastage, particularly in mutual capacitance sensing devices used for human-computer interaction, where flickering objects can generate false activation signals.
Innovation Solution
An event-based sensor system that includes a sensor array and a signal processor to classify events as meaningful or meaningless by tracking cumulative event numbers across sensing areas, discarding or flagging meaningless events associated with flickering objects, and switching between sleep and active modes based on event classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the sensor processes all activation signals generated by flickering objects, then the sensor responds to all events, but power consumption increases and resource usage increases
Solution Approach 1:
The patent extracts and removes meaningless events (flickering objects) from the stream of activation signals by comparing cumulative event numbers against thresholds, processing only meaningful events further. This eliminates unnecessary power consumption while maintaining detection of valid user inputs.
Solution Approach 2:
The patent changes the parameter of event evaluation from individual activation signals to cumulative event numbers across multiple sensing areas. By tracking and comparing cumulative counts against predetermined thresholds, the system distinguishes meaningful patterns from flickering noise, reducing power usage on meaningless events.
2Reliability
If the sensor processes all activation signals including meaningless events, then no events are missed, but resource usage increases
Solution Approach 1:
The patent extracts meaningless events from the processing pipeline by identifying sensing areas where cumulative event numbers exceed thresholds indicative of flickering. These extracted meaningless events are discarded or flagged separately, allowing efficient processing of only meaningful events while maintaining complete detection capability.
Solution Approach 2:
The patent segments the stream of activation signals into meaningful and meaningless categories based on cumulative event number analysis across sensing areas. This segmentation enables differentiated processing paths, improving resource efficiency by directing full processing resources only to meaningful events.
3Speed
If the sensor operates continuously in active mode, then all events are detected immediately, but power consumption increases
Solution Approach 1:
The patent implements periodic evaluation of cumulative event numbers against thresholds to determine transitions between sleep and active modes. This periodic monitoring enables the sensor to remain in low-power sleep mode during normal operation while quickly activating when meaningful event patterns are detected, balancing response speed with power efficiency.
Solution Approach 2:
The patent dynamically adjusts the operational mode (sleep or active) based on real-time analysis of cumulative event numbers and their rates of change. This dynamic adaptation allows the sensor to optimize between power consumption and response speed by transitioning modes according to actual event patterns rather than operating continuously.
4Use of energy by moving object
If the sensor distinguishes between meaningful and meaningless events, then power consumption is reduced, but device complexity increases
Solution Approach 1:
The patent simplifies the distinction between meaningful and meaningless events by changing the evaluation parameter from individual signal characteristics to cumulative event numbers across sensing areas. This parameter transformation reduces processing complexity while enabling effective discrimination and power optimization.
Solution Approach 2:
The patent discards meaningless events (flickering objects) identified through cumulative event number analysis, recovering processing resources for meaningful events. This selective discarding reduces overall processing complexity while maintaining detection of valid inputs, achieving power savings without proportionally increasing discrimination complexity.
Data Source
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AI summary
An event signal processing method and an event-based sensor performing the event signal processing method are provided. The event signal processing method includes receiving an activation signal to indicate sensing of an event from a sensor array, increasing the cumulative event number of a sensing area corresponding to the activation signal among sensing areas of the sensor array, reducing the cumulative event number of each of the sensing areas based on a parameter; and determining, as a flickering area, a sensing area among the sensing areas, of which the cumulative event number exceeds a threshold.