Adaptive Filter for Capacitive Input Device Noise Suppression
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Solution Overview
Problem
Capacitive sensors in input devices are susceptible to external electromagnetic noise, leading to erroneous detection of object coordinates and contact states, making it difficult to accurately detect the approach of objects like fingers or pens due to noise interference.
Innovation Solution
The input device employs a filter processing mechanism that averages degree-of-approach data over multiple cycles to suppress temporary noise-induced changes, adjusts filter response characteristics based on detected noise levels, and modifies temporal response according to the number of objects approaching the detection surface, allowing for effective noise reduction and accurate data capture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the sensor detects object approach sensitively with a simple configuration, then the detection capability is improved, but the sensor becomes susceptible to external electromagnetic noise causing erroneous detection
Solution Approach 1:
The patent applies preliminary action by performing filter processing on degree-of-approach data before using it for touch detection. The filter processing averages data over multiple detection cycles to suppress noise-induced temporary changes, preparing clean data in advance for reliable detection decisions
Solution Approach 2:
The patent implements feedback by continuously monitoring degree-of-approach data across multiple cycles and using this information to adjust filter processing parameters. The system feeds back the detected noise level and object state to dynamically control the filtering intensity, improving reliability while maintaining sensitivity
2Reliability
If filter processing is applied to reduce noise influence, then detection reliability is improved, but the response time to detect fast object motion may be delayed
Solution Approach 1:
The patent applies dynamics by making the filter processing adaptive rather than static. The filter characteristics are dynamically adjusted based on the detected noise level and the number of objects on the detection surface, allowing the system to optimize between noise suppression and response speed in real-time
Solution Approach 2:
The patent implements parameter changes by modifying filter processing parameters (such as averaging window size or filter coefficients) according to the detected state. When noise is high, stronger filtering is applied; when noise is low or objects are moving fast, filtering is reduced to maintain response speed
3Device complexity
If the filter processing uses fixed response characteristics, then the implementation is simple, but it cannot adapt to different noise levels or multiple object scenarios
Solution Approach 1:
The patent makes the filter processing dynamic by adjusting its response characteristics based on the detected number of objects and noise level. The system automatically adapts the filtering strength and temporal response to match the current usage scenario, providing versatility without requiring complex manual configuration
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 stabilizes the degree-of-approach data by reducing noise influence, enabling accurate detection of object motion even in noisy environments and facilitating fast or multiple-object input operations by optimizing filter response characteristics.
Implementation Method 1
a sensor that detects a change in capacitance can detect the approach of an object
Data Source
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AI summary
An input device capable of preventing information according to a state of approach of an object to a detection surface from being input incorrectly due to an influence of noise is provided. A series of degree-of-approach data (33) of the same object generated over a plurality of cycles of a detection operation is averaged in filter processing of the filter processing unit (26), and accordingly, the degree-of-approach data (33) after averaging is acquired. Therefore, even in a case in which the degree-of-approach data (33) is temporarily greatly changed due to an influence of noise, such a temporary change in the degree-of-approach data (33) after averaging is suppressed. Further, response characteristics of a filter in the filter processing of the filter unit (26) are changed according to a noise level 35 which is detected by a noise detection unit (25). Accordingly, since appropriate filter processing according to the noise level 35 is performed on the degree-of-approach data (33), the degree-of-approach data (33) in which the influence of noise is effectively reduced is obtained.