Clustering-based procedure for FHR monitoring.

<p>Clustering-based procedure for FHR monitoring.</p

Comparison of the results of different FHR extraction methods.

<p>Comparison of the results of different FHR extraction methods.</p

Clustering improvement example.

<p>Clustering improvement example.</p

Five-minute FHR monitoring for r08 Ab-4 AECG recording and 20-second fetal QRS complex detection.

<p>Five-minute FHR monitoring for r08 Ab-4 AECG recording and 20-second fetal QRS complex detection.</p

Clustering classification for r08 Ab-1 recording.

<p>Clustering classification for r08 Ab-1 recording.</p

Evaluation results using <i>Challenge 2013 Training Set A</i> 1-minute recordings as testing data (data for the best performing channel in each recording are shown in bold characters).

<p>Evaluation results using <i>Challenge 2013 Training Set A</i> 1-minute recordings as testing data (data for the best performing channel in each recording are shown in bold characters).</p

Scenario 1 example.

<p>(a) r08 Ab-1 preprocessed signal (b) Amplitude distance between the detected maximum followed by a minimum.</p

Example of feature selection using the filtered normalized distribution of amplitudes.

<p>(a) Case 1: selection of amplitude (50,000-sample window of r07 Ab-4 denoised recording) (b) Case 2: selection of amplitude multiplied by the number of samples (50,000-sample window of r01 Ab-4 denoised recording) (c) Case 3: selection of amplitude multiplied by the number samples (50,000-sample window of r08 Ab-4 denoised recording).</p

Application of the new method to the a03 Ab-4 recording.

<p>(a) 10-second recording (b) Clustering classification (c) Fetal RS detection after classification improvement and FP and FN correction (d) Ten-second FHR monitoring.</p

Application of the new method to the a49 Ab-2 recording.

<p>(a) Fetal RS detection after classification improvement and FP and FN correction (b) One-minute FHR monitoring for a49 Ab-2 recording.</p