ECG Signal Noise Removal via Peak Extraction and Threshold Classification
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Solution Overview
Problem
ECG sensor signals often include noise from operating and contact sources, which reduces signal reliability and delays authentication processes, such as user authentication in portable devices.
Innovation Solution
A noise removal method that extracts an ECG estimation signal based on peak values, determines comparison values using cosine distance or Euclidean distance with reference signals, and classifies the signal as ECG or noise based on threshold values to enhance signal accuracy and reliability for authentication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If ECG sensor measures signal continuously, then user authentication can be performed, but noise from device operation and contact reduces signal reliability
Solution Approach 1:
The patent extracts the harmful noise component from the sensor signal by comparing it against reference noise signals. The processor identifies and separates contact noise and operating noise from the ECG signal using correlation analysis, effectively removing these harmful factors while preserving the authentic ECG signal for reliable authentication
Solution Approach 2:
The patent introduces reference signals as intermediary elements that represent typical noise patterns. By comparing the sensor signal against these reference noise signals, the system can identify and filter out noise components without directly analyzing the complex noise itself, thus improving signal reliability
2Loss of time
If noise is present in ECG signal, then authentication process is delayed, but removing noise requires additional processing
Solution Approach 1:
The patent performs preliminary noise removal processing on the ECG signal before authentication comparison. By extracting and removing noise components in advance, the system prepares a clean authentication signal ahead of time, reducing delays during the actual authentication process while managing complexity through pre-computed reference signals
3Reliability
If threshold values are set low for noise removal, then more noise is removed, but more ECG signals may be incorrectly classified as noise
Solution Approach 1:
The patent dynamically adjusts classification thresholds based on signal characteristics and noise levels. Rather than using fixed low thresholds that could misclassify ECG signals, the system adapts threshold parameters according to the specific signal conditions, maintaining high noise removal accuracy while preserving ECG signal classification precision
Data Source
AI summary
A method and an apparatus to remove a noise from an electrocardiography (ECG) sensor signal are provided. A noise removing method includes: receiving a sensor signal collected by an electrocardiography (ECG) sensor; extracting an ECG estimation signal from the sensor signal based on a peak value of the sensor signal; determining a first comparison value between the ECG estimation signal and a first reference signal indicating an average form of ECG signals; and classifying the ECG estimation signal as one of an ECG signal and a noise by comparing the first comparison value to a first threshold value.