Capacitive Proximity Sensor Noise Synchronization
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Solution Overview
Problem
Proximity sensing devices in electronic systems face interference from noise sources like display devices, power supplies, and chargers, which obscure the signal and hinder accurate detection of input objects.
Innovation Solution
The implementation of a capacitive proximity sensing system that processes noisy sensor signals to extract a spike train, synchronizes a pulse output with the spike train, and performs proximity sensing during intervals with lower noise amplitude, thereby avoiding temporal overlap with higher noise emissions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If proximity sensing is performed continuously, then detection coverage is improved, but noise interference increases
Solution Approach 1:
The system performs proximity sensing periodically at specific time intervals rather than continuously. The sensing operations are synchronized to occur during low-noise intervals between display refresh cycles, thereby reducing noise interference while maintaining adequate detection coverage.
Solution Approach 2:
The system preliminarily identifies noise patterns and low-noise intervals before performing proximity sensing. By detecting the display refresh cycle characteristics in advance, the system can schedule sensing operations during optimal time windows with minimal noise interference.
2Speed
If sensing frequency is increased, then response speed is improved, but noise interference worsens
Solution Approach 1:
The system uses periodic sensing at strategically timed intervals rather than increasing continuous sensing frequency. By synchronizing sensing operations with low-noise periods, the system achieves fast response within acceptable timeframes without proportionally increasing noise exposure.
3Productivity
If sensing is performed during high-noise intervals, then time utilization is improved, but measurement precision deteriorates
Solution Approach 1:
The system preliminarily characterizes noise patterns and identifies low-noise intervals before performing sensing operations. This advance knowledge allows scheduling of sensing during optimal time windows, ensuring measurement precision without significantly compromising time utilization.
Solution Approach 2:
The system converts the predictable noise pattern from display refresh into a useful timing reference. By synchronizing sensing operations to occur during low-noise intervals between refresh cycles, the system transforms the harmful noise pattern into a beneficial timing structure that improves measurement precision.
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
This approach enhances the accuracy of proximity sensing by reducing noise interference, allowing for reliable detection of input objects even in noisy environments without requiring a direct synchronization output from noise sources.
Implementation Method 1
a capacitive proximity sensor comprising a plurality of transmitter electrodes and a plurality of receiver electrodes for proximity sensing in a sensing region
Data Source
AI summary
An input device includes a capacitive proximity sensor and a processing system. The capacitive proximity sensor includes a multitude of transmitter electrodes and a multitude of receiver electrodes for proximity sensing in a sensing region. The processing system is configured to obtain a noisy sensor signal from the capacitive proximity sensor, extract a spike train in the noisy sensor signal, synchronize a pulse output of a pulse-generating circuit onto the spike train, and triggered by a first of a multitude of pulses of the pulse output, perform a first capacitive proximity sensing.