Algorithm 1. Annotating sleep apnea events based on QRS complex counts in ECG signals

Input qrs_annotations (sample indices) sampling_rate (samples per second) time_window (duration of each window in seconds) QRS_threshold (minimum QRSD count threshold to avoid labels) Output: apnea_annotations (list of labels: Apnea and normal lables) Step: 1. window_size = time_window * sampling_rate 2. Determine num_windows = len(qrs_annotations)//window_size  3. Initialize an empty labels list called apnea_annotations = [] 4. For each window i from 0 to num_window −1, do as follows:    4.1 Set time start_sample = i * window_size    4.2 Set end_sample = start_sample + window_size    4.3 Count QRS in the current time window within start_sample, end_sample    4.4 if QRS_count < QRS_threshold , then     4.4.1 append apnea_annotations.append((‘A’, start_sample))    Else     4.4.2 apnea_annotations.append((‘N’, start_sample))