Linda Rattfält

Electrical characteristics of conductive yarns and textile electrodes for medical applications

Clothing with conductive textiles for health care applications has in the last decade been of an upcoming research interest. An advantage with the technique is its suitability in distributed and home health care. The present study investigates the electrical properties of conductive yarns and textile electrodes in contact with human skin, thus representing a real ECG-registration situation. The yarn measurements showed a pure resistive characteristic proportional to the length. The electrodes made of pure stainless steel (electrode A) and 20% stainless steel/80% polyester (electrode B) showed acceptable stability of electrode potentials, the stability of A was better than that of B. The electrode made of silver plated copper (electrode C) was less stable. The electrode impedance was lower for electrodes A and B than that for electrode C. From an electrical properties point of view we recommend to use electrodes of type A to be used in intelligent textile medical applications.

Electrical Properties of Textile Electrodes

In this study we aim to explain the behavior of textile electrodes due to their construction techniques. Three textile electrodes were tested for electrode impedance and polarization potentials. The multifilament yarn (A) is favorable for its low thread resistance. Although, when knitted into electrodes, the staple fiber yarn (B) showed a comparable and satisfiable electrode impedance. The multifilament yarn had however a lower polarization potential drift then the other specimens. The monofilament yarn (C) had high electrode impedance and varying mean polarization potentials due to its conductive material and small contact area with the skin.

Robust Heartbeat Detector Based on Weighted Correlation and Multichannel Input: Implementation on the ECG Recorded with Textile Electrodes

The aim of this study was to develop and evaluate a robust heartbeat detector for noisy electrocardiograms (ECGs) recorded with textile electrodes. The authors suggest a method based on weighted correlation in a multi-channel ECG to obtain a heartbeat detector. Signals were acquired during rest and at movements which simulate every day activities. From each recording a segment corresponding to a heartbeat was extracted and correlated with the whole signal. From the correlation data, heartbeat candidates were derived and weighted based on their variance similarity with the heartbeat model and previous heartbeats. Finally, the outputs of each channel were added to create the global output. The output was compared to the Pan Tompkins heartbeat detector. Results are promising for recordings at rest (sensitivity = 0.97, positive predictive value (PPV) = 0.97). For static muscle tension in the torso the results were much higher than the reference method (sensitivity = 0.77, PPV = 0.85). Corresponding values for the reference method were sensitivity = 0.96 and PPV = 0.95 at rest and sensitivity = 0.52 and PPV = 0.75 during muscle tension.

Electrical Characterization of Screen Printed Electrodes for ECG Measurements

Screen printed electrodes with conductive ink made of Carbon and Ag/AgCl were tested for polarization potentials and electrode impedances. In 30 minutes the mean decrease of polarization potential was 2 mV. The electrode impedances at 10 Hz were between 670 and 250 Ohms. These characteristics seem adequate for personalized health care applications.

A platform for physiological signals including an intelligent stethoscope

We have developed a physiological signal platform where presently phonocardiographic (PCG) and electrocardiographic (ECG) signals can be acquired and on which our signal analysis techniques can be implemented. The platform can also be used to store patient data, to enable comparison over time and invoke distance consultation if necessary. Our studies so far indicate that with our signal analysis techniques of heart sounds we are able to separate normal subject from those with aortic stenosis and mitral insufficiency. Further we are able to identify the third heart sound. The platform is being tested in a primary health care setting.

A platform for patient monitoring in home health care including an interpretation tool for heart failure patients

About 2% of the population suffer from heart failure, which is a disease associated with high mortality. We have developed a measurement platform including an interpretation tool for heart failure patients where physiological signals can be acquired and on which signal analysis techniques can be implemented. The platform can also be used to store patient data, to enable comparison over time and invoke distance consultation if necessary. In this platform, we have implemented a tool for interpretation support of the data measured from the patient. This tool are intended for use in home health care as an aid for monitoring and follow up heart failure patients.