Tensorflow implementation for ECG sleep apnea detection

• Tensorflow 2.5

• Python 3.9

• 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 https://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