Sensor Signal Restoration Using 2D Normal Distribution Waveforms
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Solution Overview
Problem
Multimedia electronic devices face challenges in accurately detecting touch inputs due to unstable sensing signals, particularly in low ground mass states where signal peaks are concave and noisy, leading to reduced accuracy in coordinate calculation.
Innovation Solution
A sensor system with enhanced sensing performance is introduced, featuring a sensor layer with first and second electrodes, a signal detection circuit, a signal state detector, a signal restorer using a 2D normal distribution waveform, and a coordinate calculator. This system converts sensing signals into data, detects signal states, restores data using a 2D normal distribution waveform, and calculates coordinates based on the restored data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional signal detection is used in low ground mass states, then the sensor can operate with simple hardware, but the sensing accuracy deteriorates due to concave and noisy signal peaks
Solution Approach 1:
The patent applies preliminary action by detecting the signal state before coordinate calculation and restoring the signal data in advance. The signal restorer reconstructs concave signal peaks using stored statistical values and 2D normal distribution waveforms before the coordinate calculator processes the data, ensuring accurate touch detection without requiring complex real-time processing hardware
Solution Approach 2:
The patent implements feedback by storing statistical values (mean, standard deviation) of sensing signals in memory and using them to restore subsequent signals. The signal state detector continuously monitors signal quality and provides feedback to the signal restorer, which adjusts restoration parameters based on the detected state, creating a closed-loop system that improves measurement precision
2Measurement precision
If signal restoration using 2D normal distribution waveform is applied, then the positioning precision is improved, but the computational complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing 2D normal distribution waveforms and their statistical parameters in memory during manufacturing or initial operation. During actual touch detection, the system retrieves these pre-computed waveforms and applies them directly to restore signal peaks, avoiding the need for complex real-time 2D normal distribution calculations and reducing computational complexity
Solution Approach 2:
The patent uses copying by creating a mathematical model (2D normal distribution waveform) of the expected signal peak shape and storing it in memory. When a concave signal peak is detected, the system copies this pre-defined waveform model and applies it to restore the distorted signal, replacing complex real-time mathematical transformations with simpler data retrieval and application operations
Data Source
AI summary
A sensor including: a sensor layer including a first electrode and a second electrode; a signal detection circuit configured to convert a sensing signal received from the sensor layer into data; a signal state detector configured to detect a state of the sensing signal based on the data; a signal restorer configured to output restoration data by restoring the data depending on the state of the sensing signal; and a coordinate calculator configured to calculate coordinates corresponding to the sensing signal based on the data or the restoration data, wherein the signal restorer restores the data into the restoration data by using a 2-dimensional (2D) normal distribution waveform.