1-D Convoltional Neural network for ECG signal processing

206 views (last 30 days)
shahram taheri
shahram taheri on 11 Oct 2017
Answered: David Willingham on 15 Nov 2021
Dear Sir, I read the useful comment in https://www.mathworks.com/matlabcentral/answers/331164-convolutional-1d-net by Joss Knight. I want to use 1-D for ECG classification. I have 5 classes of signal,each one has 651 samples, I want to simulate the proposed method of the following article: "Application of Deep Convolutional Neural Network for Automated Detection of Myocardial Infarction Using ECG Signals" by Prof. Rajendra Acharya. In their paper, they mentioned the CNN structure as follow:
I worte the following code in order to define my CNN layers:(assumed that input signal has 651 samples)
layers = [imageInputLayer([1 651])
convolution2dLayer([1 102],3,'stride',1)
maxPooling2dLayer([1 2],'stride',2)
convolution2dLayer([1 24],10,'numChannels',3)
maxPooling2dLayer([1 2],'stride',2)
convolution2dLayer([1 11],10,'stride',1,'numChannels',10)
maxPooling2dLayer([1 2],'stride',2)
convolution2dLayer([1 9],10,'numChannels',10)
maxPooling2dLayer([1 2],'stride',2)
fullyConnectedLayer(30)
fullyConnectedLayer(10)
fullyConnectedLayer(2)
softmaxLayer
classificationLayer];
is it correct? I train my CNN with these layers, but the predicted labels are fixed to one of the classes! But when I use ony the 4 first layers, the accuracy is very good(98.35%). what happend when I insert the remaining layers?
  2 Comments
Mirko Job
Mirko Job on 29 Mar 2020
Dear Sir,
I am also working with convolutional networks for 1D signal classification, but i'm trying to do it on a time series. I was thinking to format my signal as a 1 x 1 x N°Features x Time observations, but then i am confused on how to define the filter on the convolutional layer to make it operate on the 4D. Is in your opinion the formatting of my data correct or i am just over-complicating something far more simple?

Sign in to comment.

Answers (5)

Pavithra R
Pavithra R on 12 Dec 2017
I have completed the feature extraction of ECG. Now I have to classify those using CNN. Kindly give a sample code for reference.
  3 Comments
hilal duran
hilal duran on 25 Mar 2019
I agree with shahram taheri , and also you can use LSTM to claffify ECG signal.

Sign in to comment.


shefali saxena
shefali saxena on 6 Nov 2018
hi shahram, as i am new to Deep Learning can you help me on how we can give 1d (ECG) signal as a input to CNN

Kaouter Karboub
Kaouter Karboub on 13 Sep 2019
Dear friends ,
first of all, for those who asked about how CNN extract features, well ... its too simple , if u ve got a simple look in any CNN architecture u can figure it out that in any CNN layer the main objective is to extract features and that the classification is not done til the last layer which is obviously the output layer
second , about the 1 d signals , yes u can for sure use CNN .. by using those samples, plot them and use CWT and then fit them into ur CNN .....
main rule in here : every classification task needs a preprocessing of ur data that can be 1 d or 2 d or 3d ... it doesn t matter !!
  1 Comment
Asaf Raza
Asaf Raza on 5 Mar 2021
How i can classify hand crafted features with pretrain deep neural netwrok .

Sign in to comment.


S.RAMA SURYA VAMSI
S.RAMA SURYA VAMSI on 15 Nov 2021
in matlab,write a program to generate a ecg and convolution with exponential wave and find its psd and find its fourier series,laplace transform,z transform

Tags

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!