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The purpose of this paper was to offer more reliable dry electrode materials for long-term measuring and determine how repeated machine washing affects the measured impedance and surface resistance of the sample electrodes. The aim was to manufacture electrodes that could be used for the measurement of ECG. Skin friendly, metal sheet type, electrodes could be a solution.

In addition to two conventional electrodes already used in heart rate belts, the authors prepared and tested three different sheet metal electrodes. Three 20-mm-diameter electrodes were manufactured from the following materials: silvered knit, conductive polymer, stainless steel, silver and platinum. Electrode impedance was measured at seven frequencies from 1 Hz to 1 MHz, by placing two electrodes face-to-face. Measurements were taken on unused electrodes and after multiple machine washes at 40°C.

Analysis of the measurements indicates that with every material tested, the impedances are elevated after repeated washes. All metallic materials have impedances in the range of 0.01 to 4.5 Ω. Metal sheet electrodes can be integrated comfortably into the textile, and they endure textile maintenance without loss of electrical properties.

Metal sheet electrodes function well in long-term vital signs monitoring, provide a reliable signal and are resistant to maintenance. For the reasons described in this research, they can be used as a long-term wearable sensor.

Novel electrode material for long-term measuring research is important in many disciplines such as health care and apparel manufacturing. These findings suggest that pure metal electrodes are better than conductive textiles in long-term measuring.

Wearables are gaining prominence in the health-care industry and their use is growing. The elderly and other patients can use these wearables to monitor their vitals at home and have them sent to their doctors for feedback. Many studies are being conducted to improve wearable health-care monitoring systems to obtain clinically relevant diagnoses. The accuracy of this system is limited by several challenges, such as motion artifacts (MA), power line interference, false detection and acquiring vitals using dry electrodes. This paper aims to focus on wearable health-care monitoring systems in the literature and provides the effect of MA on the wearable system. Also presents the problems faced while tracking the vitals of users.

MA is a major concern and certainly needs to be suppressed. An analysis of the causes and effects of MA on wearable monitoring systems is conducted. Also, a study from the literature on motion artifact detection and reduction is carried out and presented here. The benefits of a machine learning algorithm in a wearable monitoring system are also presented. Finally, distinct applications of the wearable monitoring system have been explored.

According to the study reduction of MA and multiple sensor data fusion increases the accuracy of wearable monitoring systems.

This study also presents the outlines of design modification of dry/non-contact electrodes to minimize the MA. Also, discussed few approaches to design an efficient wearable health-care monitoring system.