Proximity Sensing with Reflected Light Patterns for Still-Hand Detection
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Solution Overview
Problem
Existing proximity sensors cannot recognize user motions while determining proximity, as they rely on measuring light quantity changes, which fails when the user is not moving.
Innovation Solution
A proximity sensor with a quantity change detection unit that detects changes in reflected light intensity and a proximity determination unit that uses event occurrence numbers and temporal distribution patterns to determine proximity, along with a motion recognition unit that identifies motion based on these changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a proximity sensor measures light quantity changes to determine proximity, then proximity determination is achieved, but motion recognition capability is lost when the user is not moving
Solution Approach 1:
The system dynamically switches between two operating modes: proximity determination mode (using light quantity changes) and motion recognition mode (using temporal distribution patterns of events). This dynamic adaptability allows the sensor to perform both functions effectively depending on the operational context, resolving the contradiction between precise proximity measurement and motion recognition capability.
Solution Approach 2:
The same light detection unit serves dual purposes: it detects light quantity changes for proximity determination and detects temporal distribution patterns of events for motion recognition. This multi-functionality eliminates the need for separate sensors, allowing the system to achieve both proximity accuracy and motion recognition capability through a single integrated device.
2Use of energy by moving object
If a sensor detects light quantity changes without measuring absolute values, then energy consumption is reduced, but distance measurement capability is lost when the object is stationary
Solution Approach 1:
The system uses periodic modulation of the light source intensity, creating rhythmic light quantity changes that reflect both proximity and motion information. By analyzing the temporal distribution of events within each modulation period, the system can distinguish between stationary proximity measurements and motion detection, maintaining energy efficiency while recovering distance measurement capability for stationary objects.
Solution Approach 2:
The system incorporates feedback mechanisms that analyze the temporal patterns of detected light events and adjust the interpretation of light quantity changes accordingly. This feedback allows the system to compensate for the lack of absolute light value measurements by using relative temporal patterns, thereby recovering distance measurement capability while maintaining low energy consumption.
3Device complexity
If proximity determination uses only light quantity changes, then device complexity is reduced, but the ability to recognize both motion and stationary proximity is compromised
Solution Approach 1:
The system dynamically processes the same light detection data in two different ways: analyzing light quantity changes for proximity determination and analyzing temporal distribution patterns for motion recognition. This dynamic processing approach maintains simple hardware architecture while achieving dual functionality, as the complexity is managed through software/algorithms rather than additional hardware components.
Solution Approach 2:
A single light detection unit performs multiple functions by analyzing different characteristics of the detected light signals. The same detector analyzes both the magnitude of light quantity changes (for proximity) and the temporal distribution patterns of events (for motion recognition), achieving dual functionality without increasing device complexity.
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
Enables the recognition of user motions and accurate proximity determination, even when the user is not moving, by analyzing changes in reflected light intensity and event patterns.
Implementation Method 1
a quantity change detection unit which detects a change in quantity of a reflected light which is an output light, of which intensity changes, reflected by an object
Data Source
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AI summary
A proximity sensor and proximity sensing method using a change in light quantity of a reflected light are disclosed. The proximity sensor may include a quantity change detection unit which detects a change in a quantity of reflected light which is output light which has been reflected by an object, where an intensity of the output light changes, and a proximity determination unit which determines a proximity of the object to the quantity change detection unit based on a change in the intensity of the output light and the detected change in the quantity of the reflected light.