https://github.com/mr-mohan-v/ecg-noise-filter

Noise reduction in ECG signal using Finite Impulse Response(FIR) filter
https://github.com/mr-mohan-v/ecg-noise-filter

filters python3 signalprocessing

Last synced: about 2 months ago
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Noise reduction in ECG signal using Finite Impulse Response(FIR) filter

• Host: GitHub
• URL: https://github.com/mr-mohan-v/ecg-noise-filter
• Owner: mr-mohan-v
• Created: 2022-02-10T14:41:41.000Z (about 3 years ago)
• Default Branch: master
• Last Pushed: 2023-02-28T15:52:47.000Z (about 2 years ago)
• Last Synced: 2025-01-05T16:33:28.714Z (4 months ago)
• Topics: filters, python3, signalprocessing
• Language: Python
• Homepage:
• Size: 157 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# ECG-Noise-filter

# Abstract :

    Noise reduction in ECG signal using Finite Impulse Response(FIR) filter

             ~The electrocardiogram (ECG) signal is non-stationary

             electrical signals from the heart characteristically 

             precede the normal mechanical function and monitoring

             of these signals has great clinical significance.

# Motivation:

             ~The heart rate analysis from an ECG is crucial in

             assessing the health condition of an individual. 

             

             ~But the measured ECG tend to have noises such as

             the 50Hz interference and the DC.  

             

             ~These noises make the detection of peaks inaccurate

             which in turn make the detection of heartrate inaccurate.

             

             ~Thus, removing the noises from the ECG is pertinent

             for the proper analysis of the ECG signal.

             

             ~We have used FIR filter to achieve filtration of ECG signal.

# System description with application :

             ~The Electrocardiogram (ECG) machine with 4 terminal wires is

             an electrogram of the heart which is a graph of voltage versus time

             of the electrical activity of the heart using electrodes placed on the skin.

             These electrodes detect the small electrical changes.

             

             ~But the signal have power line interference which have 50Hz frequency

             and DC which make the detection of heartrate inaccurate.

             

             ~The finite impulse response (FIR) filter is created to remove the

             50Hz interference as well as the DC from the signal. 

             

             ~We used bandpass filter  for the calculation of impulse response of

             the desired frequency response created and Hamming window for normalising

             the impulse response which is used for convolution of ECG signal and impulse response. 

For the values of ECG signal passed to the system -> Filtered signal values that can be displayed is returned

# Methodology :

            ~FIR filters are digital filters with finite impulse response.

            

            ~They are also known as non-recursive digital filters because of their

            inherent stability when implement in non-recursive form, the ease with 

            which one can attain linear phase and more stable which cant be achieved in IIR filter.

            

            ~This filter doesn’t depend on past samples of input along with past output like the IIR filter.

            

            ~Bandstop filter is a combination of lowpass and highpass filter 

            which can block or at least severely attenuate a band of frequencies within 

            the two cut-off frequency points specified and allow frequencies other than that.  

            

            ~The Hamming window is a taper formed by using a weighted cosine 

            which reduces the ripple on either side of the peak.

            

            ~Then, the ECG signal and impulse response is passed to a function 

            that does convolution and returns the filtered signal.