ECG Signal Quality in Intermittent Long-Term Dry Electrode Recordings with Controlled Movement Artifacts

Published: 2 March 2023| Version 1 | DOI: 10.17632/j9rt95468p.1
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Description

Wearable long-term monitoring applications are becoming more and more popular in both consumer and medical markets. In wearable ECG monitoring the data quality is dependent on the properties of the electrodes and how they contact the skin. Dry electrodes do not require any action from the user. They usually do not irritate the skin and they provide sufficiently high-quality data for ECG monitoring purposes during low user activity. We investigated prospective movement artifact resistant dry electrode materials for wearable ECG monitoring. The tested materials were 1) porous: conductive polymer, conductive silver fabric, conductive silver fabric with moisture retaining membrane and 2) solid: stainless steel, silver, and platinum. ECG was acquired from test subjects in a 10-minute continuous settling test and in a 48-hour intermittent long-term test. In the settling test the electrodes were stationary, whereas in the long-term test both stationary and controlled movement artifact tests were included. Signal-to-noise ratio (SNR) was used as a figure of merit to quantify the results. The SNR increased in all the electrode types during the settling test. In the long-term test the SNR was in general elevated further. The introduction of electrode movement reduced the SNR markedly. Solid electrodes had higher SNR than the porous electrodes. In the stationary testing stainless steel showed the highest SNR followed by platinum, silver, conductive polymer and conductive fabric. In the movement testing the platinum and stainless steel changed places and the rest of the order was the same. The files include a video showing the instrumentation during movement testing and ECG recording and an Excel-sheet with the calculated signal-to-noise results. Full methods are described in the related research paper of the same name.

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Full methods are described in the related research paper of the same name.

Institutions

Tampereen yliopisto

Categories

Signal Processing, Biomedical Engineering, ECG Electrode, Wearable Sensor

Funding

Tampere University Hospital Support Foundation

MK355

Tampere Universtity, Faculty of Medicine and Health Technology

(no grant number)

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