A NOVEL METHOD FOR MOTION ARTIFACT REMOVAL IN WEARABLE PPG SENSORS BASED ON BLIND SOURCE SEPARATION

The recent development of healthcare systems has provided a significant contribution to ambulatory patient monitoring. In that context, signal quality and disturbances induced by noise or motion artifacts play an important role in the field of signal processing tasks. Especially the Photoplethysmogram (PPG) is very liable to movement artifacts which severely hamper the extraction of vital parameters like the heart rate or oxygen saturation. To record patient movements, an innovative sensor system is proposed, which acquires accelerometer data next to the PPG. As in Adaptive Noise Cancelers, we propose to use the acceleration as reference to recover corrupted PPGs by means of the Blind Source Separation. Sophisticated methods of ICA have been used, resulting in a novel approach for artifact suppression in the PPG that has been tested on laboratory datasets.