Optimal Cutoff Frequency for Static Noise Detection in ECG Signals?
Hello MATLAB Community,
I am currently working on optimizing the detection of static noise in ECG signals and would greatly appreciate your expertise. Specifically, I am looking to determine the best cutoff frequency for filtering this noise. Below, I have listed the SNR (Signal-to-Noise Ratio) values for different cutoff frequencies in two leads, Lead I and Lead aVL:
Cutoff Frequency = 0.5 Hz
SNR in Lead I: 7.98 dB
SNR in Lead aVL: 5.41 dB
Cutoff Frequency = 1.0 Hz
SNR in Lead I: 7.29 dB
SNR in Lead aVL: 5.11 dB
Cutoff Frequency = 5.0 Hz
SNR in Lead I: 4.03 dB
SNR in Lead aVL: 3.23 dB
Cutoff Frequency = 10.0 Hz
SNR in Lead I: 2.17 dB
SNR in Lead aVL: 1.96 dB
Quantification of Noise:
Cutoff Frequency = 0.5 Hz
Number of noise points in Lead I: 299
Number of noise points in Lead aVL: 341
Cutoff Frequency = 1.0 Hz
Number of noise points in Lead I: 278
Number of noise points in Lead aVL: 304
Cutoff Frequency = 5.0 Hz
Number of noise points in Lead I: 179
Number of noise points in Lead aVL: 213
Cutoff Frequency = 10.0 Hz
Number of noise points in Lead I: 127
Number of noise points in Lead aVL: 137
Additionally, I have attached an image showing the residuals ( lead I ) .
To determine the best threshold value, I used an approach based on minimizing the number of noise points detected in the filtered signal. Here is a detailed explanation of the process:
Process to determine the best threshold value
Calculation of the filtered signal:
For each cutoff frequency, I applied a high-pass filter to remove low-frequency components from the ECG signal.
Threshold definition:
I tested different threshold values, defined as multiples of the standard deviation (STD) of the filtered signal. The tested thresholds were 0.25 * STD, 0.5 * STD, 0.75 * STD, and 1 * STD.
Noise point detection:
For each threshold value, I detected points in the filtered signal where the amplitude exceeds the threshold.
The number of detected noise points is counted for each threshold value.
Selection of the best threshold:
The best threshold is the one that minimizes the number of detected noise points. The hypothesis is that the optimal threshold eliminates noise without affecting the useful components of the ECG signal.
Based on this data, I am seeking advice on the most suitable cutoff frequency for effectively reducing static noise while preserving the integrity of the ECG signal. Any suggestions or insights into methodologies for determining this would be highly valuable.
Thank you in advance for your help!
Best regards,Hello MATLAB Community,
I am currently working on optimizing the detection of static noise in ECG signals and would greatly appreciate your expertise. Specifically, I am looking to determine the best cutoff frequency for filtering this noise. Below, I have listed the SNR (Signal-to-Noise Ratio) values for different cutoff frequencies in two leads, Lead I and Lead aVL:
Cutoff Frequency = 0.5 Hz
SNR in Lead I: 7.98 dB
SNR in Lead aVL: 5.41 dB
Cutoff Frequency = 1.0 Hz
SNR in Lead I: 7.29 dB
SNR in Lead aVL: 5.11 dB
Cutoff Frequency = 5.0 Hz
SNR in Lead I: 4.03 dB
SNR in Lead aVL: 3.23 dB
Cutoff Frequency = 10.0 Hz
SNR in Lead I: 2.17 dB
SNR in Lead aVL: 1.96 dB
Quantification of Noise:
Cutoff Frequency = 0.5 Hz
Number of noise points in Lead I: 299
Number of noise points in Lead aVL: 341
Cutoff Frequency = 1.0 Hz
Number of noise points in Lead I: 278
Number of noise points in Lead aVL: 304
Cutoff Frequency = 5.0 Hz
Number of noise points in Lead I: 179
Number of noise points in Lead aVL: 213
Cutoff Frequency = 10.0 Hz
Number of noise points in Lead I: 127
Number of noise points in Lead aVL: 137
Additionally, I have attached an image showing the residuals ( lead I ) .
To determine the best threshold value, I used an approach based on minimizing the number of noise points detected in the filtered signal. Here is a detailed explanation of the process:
Process to determine the best threshold value
Calculation of the filtered signal:
For each cutoff frequency, I applied a high-pass filter to remove low-frequency components from the ECG signal.
Threshold definition:
I tested different threshold values, defined as multiples of the standard deviation (STD) of the filtered signal. The tested thresholds were 0.25 * STD, 0.5 * STD, 0.75 * STD, and 1 * STD.
Noise point detection:
For each threshold value, I detected points in the filtered signal where the amplitude exceeds the threshold.
The number of detected noise points is counted for each threshold value.
Selection of the best threshold:
The best threshold is the one that minimizes the number of detected noise points. The hypothesis is that the optimal threshold eliminates noise without affecting the useful components of the ECG signal.
Based on this data, I am seeking advice on the most suitable cutoff frequency for effectively reducing static noise while preserving the integrity of the ECG signal. Any suggestions or insights into methodologies for determining this would be highly valuable.
Thank you in advance for your help!
Best regards, Hello MATLAB Community,
I am currently working on optimizing the detection of static noise in ECG signals and would greatly appreciate your expertise. Specifically, I am looking to determine the best cutoff frequency for filtering this noise. Below, I have listed the SNR (Signal-to-Noise Ratio) values for different cutoff frequencies in two leads, Lead I and Lead aVL:
Cutoff Frequency = 0.5 Hz
SNR in Lead I: 7.98 dB
SNR in Lead aVL: 5.41 dB
Cutoff Frequency = 1.0 Hz
SNR in Lead I: 7.29 dB
SNR in Lead aVL: 5.11 dB
Cutoff Frequency = 5.0 Hz
SNR in Lead I: 4.03 dB
SNR in Lead aVL: 3.23 dB
Cutoff Frequency = 10.0 Hz
SNR in Lead I: 2.17 dB
SNR in Lead aVL: 1.96 dB
Quantification of Noise:
Cutoff Frequency = 0.5 Hz
Number of noise points in Lead I: 299
Number of noise points in Lead aVL: 341
Cutoff Frequency = 1.0 Hz
Number of noise points in Lead I: 278
Number of noise points in Lead aVL: 304
Cutoff Frequency = 5.0 Hz
Number of noise points in Lead I: 179
Number of noise points in Lead aVL: 213
Cutoff Frequency = 10.0 Hz
Number of noise points in Lead I: 127
Number of noise points in Lead aVL: 137
Additionally, I have attached an image showing the residuals ( lead I ) .
To determine the best threshold value, I used an approach based on minimizing the number of noise points detected in the filtered signal. Here is a detailed explanation of the process:
Process to determine the best threshold value
Calculation of the filtered signal:
For each cutoff frequency, I applied a high-pass filter to remove low-frequency components from the ECG signal.
Threshold definition:
I tested different threshold values, defined as multiples of the standard deviation (STD) of the filtered signal. The tested thresholds were 0.25 * STD, 0.5 * STD, 0.75 * STD, and 1 * STD.
Noise point detection:
For each threshold value, I detected points in the filtered signal where the amplitude exceeds the threshold.
The number of detected noise points is counted for each threshold value.
Selection of the best threshold:
The best threshold is the one that minimizes the number of detected noise points. The hypothesis is that the optimal threshold eliminates noise without affecting the useful components of the ECG signal.
Based on this data, I am seeking advice on the most suitable cutoff frequency for effectively reducing static noise while preserving the integrity of the ECG signal. Any suggestions or insights into methodologies for determining this would be highly valuable.
Thank you in advance for your help!
Best regards, ecg, signal processing, noises, static_noise, ptb_xl, snr MATLAB Answers — New Questions
