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ECG Sleep Apnea Detection

Tensorflow implementation for ECG sleep apnea detection

Prerequisites

ECG Sleep Apnea Dataset

  • The data in the directory have been contributed by Dr. Thomas Penzel of Phillips-University, Marburg, Germany.
  • 35 records (a01 through a20, b01 through b05, and c01 through c10)
  • 7 hours to 10 hours of ECG signal, a set of apnea annotations, a set of machine-generated QRS annotations
  • .dat files: ECG signal (16 bits per sample, Fs=100Hz)
  • .apn files: binary annotation files containing an annotation for each minute of each recording the presence or absence of apnea
  • .qrs files: machine generated binary annotation files, made using sqrs125
wget -r -np http://www.physionet.org/physiobank/database/apnea-ecg/

Getting Started

Pre-processing

  • RR Interval: extracting the time intervals between consecutive heart beats
  • QRS Amplitude: calculates the amplitude of R-peak
  • Age and Sex
python pre_proc.py

Train

  • Train a model:
python train.py