Article ID Journal Published Year Pages File Type
4973598 Biomedical Signal Processing and Control 2017 11 Pages PDF
Abstract
This paper proposes a novel flexible touch sensor based on conductive elastomer (CE) for biomedical applications. The CE electrodes are simple and easy to use, and made of a silver-coated glass (Ag/G) composite material. The purpose of this work is to produce a novel dry electrode, where skin preparation is not needed anymore in order to avoid the skin from becoming irritated. The CE electrode has a length of 55 mm and width of 35 mm. The surface resistivity of the CE electrode is 0.2 ohm/sq. The proposed system does not require additional active electrodes, and a single-layer standard printed circuit board (PCB) was developed to allow for portable electrocardiography (ECG) and electromyography (EMG) signal acquisition. The proposed electrodes, used in contact with the fingertips, are demonstrated and evaluated for the biopotential monitoring applications of long-term ambulatory ECG from fingertips and EMG signal from human index finger to control man-machine interface device. We used two CE electrodes for obtaining ECG signal from fingertips and another electrode is used on the left leg. In case of EMG signal acquisition, we used two CE electrodes on the index, ring finger and another electrode is used for reference. We measured the impedance as per the frequency change and compared the outcomes with those of Ag/AgCl electrodes. Afterward, we measured the ECG signal and investigated possible artifacts caused by motion. Skin-electrode impedance of the CE was measured and compared to the Ag/AgCl electrodes, where we found lower impedance for CE electrodes. In addition, the power spectrum of the biopotential signals obtained from the CE electrodes are evaluated and compared to those obtained with Ag/AgCl electrodes for estimating signal quality. The results indicate that the proposed touch sensor is capable of bringing a good quality biopotential signals.
Related Topics
Physical Sciences and Engineering Computer Science Signal Processing
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