Textile electrodes integrated into clothes are an innovative approach for mobile ECG monitoring. However, the lack of electrode fixation on the skin causes high susceptibility to artifacts due to movements and changing electrochemical characteristics of the textile electrodes. In this paper we compare different artifact removal approaches concerning their efficiency in realistic multichannel ECG recordings acquired with textile electrodes. We employed Principal Component Analysis (PCA) and Independent Component Analysis (ICA) in time and frequency domain using FastICA and Temporal Decorrelation Source Separation (TDSEP), respectively. Using textile electrodes comprising silver-coated fibers, five Einthoven-I-leads were acquired during walking, running and extensive breathing. Horizontally aligned electrodes each located on the left and right side of the shoulders, the chest and the back obtain the ECG signals. A reference signal was recorded using self-adhesive Ag/AgCl electrodes placed at the inner forearms enabling calculation of the correlation coefficient and the R-peak detection error. The methods using ICA enhance ECG recordings acquired with textile electrodes for all test conditions. TDSEP in the time domain obtains the best results and successfully removes artifacts in recordings of extensive breathing and walking. The results during running show considerable improvements but no complete artifact separation. In conclusion, ICA represents a promising approach for artifact reduction in multichannel ECG recordings acquired with textile electrodes.
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This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.