Tensorflow implementation for ECG sleep apnea detection
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Tensorflow 2.5
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Python 3.9
- 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/- 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 a model:
python train.py