All Projects → vinayakumarr → Signal-Processing-and-Pattern-Classification

vinayakumarr / Signal-Processing-and-Pattern-Classification

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Signal-Processing-and-Pattern-Classification - Atrial fibrillation & PCG classification

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Signal-Processing-and-Pattern-Classification

DOI

Please cite the following papers, if you use the code as part of your research

Real-Time Detection of Atrial Fibrillation from Short Time Single Lead ECG Traces Using Recurrent Neural Networks

Instantaneous Heart Rate as a Robust Feature for Sleep Apnea Severity Detection using Deep Learning

Single Sensor Techniques for Sleep Apnea Diagnosis using Deep Learning

Anomaly detection in Phonocardiogram employing Deep learning

Deep models for Phonocardiography (PCG) classification

Atrial Fibrillation: Data set is from https://physionet.org/physiobank/database/afdb/

PCG-physionet: Data set is from https://physionet.org/challenge/2016/

Sleep Apnea: Data set is from https://www.physionet.org/physiobank/database/apnea-ecg/

heartsound - PCG: Data set is from http://www.peterjbentley.com/heartchallenge/

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Software Installation

sudo apt-get install libatlas-base-dev gfortran python-dev

sudo apt-get install python-pip

sudo pip install --upgrade pip

sudo pip install numpy

sudo pip install scipy

sudo pip install matplotlib

Sudo pip install seaborn

sudo pip install scikit-learn

sudo pip install tensorflow

sudo pip install theano

sudo pip install keras

sudo pip install pandas

sudo pip install h5py

sudo pip install jupyter

sudo pip install ipython

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