Textile electrodes for ECG measurements in distributed care, performance and applications

Sammanfattning: The aim of this thesis work has been to explore textile electrodes for electrocardiographic (ECG) measurements both in terms of their electrode properties and possibility to further improve their robustness to noise with signal processing techniques. Previous research within the field has shown that acquisition of ECG is possible with textile electrodes, but little attention has been focused on how they function and especially if movements are included in the measurement protocol.In a first study, the electrical properties of conductive textiles were evaluated in the same manner as conventional Ag/AgCl ECG electrodes. Three yarns and textile electrode surfaces were tested. The electrodes made from pure stainless steel (A) and 20% stainless steel/ 80% polyester (B) showed acceptable stability of electrode potentials. The electrode made from silver plated copper (C) was less robust. The best electrode impedance characteristic had Electrode A and hence from an electrical properties point of view we recommend electrodes of type A to be used for ECG measurements.The second paper contains an application of canonical correlation analysis (CCA) on multi channel ECG signals recorded with textile electrodes. Using CCA to solve the blind source separation (BSS) problem, we intended to separate the ECG signal from the various noise sources. The method (CCABSS) was compared to averaging of the ECG channels and to the independent component analysis method (ICA). Results show a loss of the ECG signal while simulating various noise in 33%, 17% and 7% of the cases for averaging, ICA and CCA, respectively.A drawback with the CCABSS approach is however that it produces many outputs and that information regarding the wanted feature to detect is not included in the analysis. In the third article, an event detector based on a multichannel input, a model of the event and weighted correlation was used instead. For measurements at rest and upper body rotation, the sensitivity was 100% and 99% respectively. Muscle tension and walking were the hardest to detect with a sensitivity of 88% and 91% respectively.