Casadei, Valentina 
ORCID: 0000-0001-6391-8829 and Ferrero, Roberto ORCID: 0000-0001-7820-9021
(2022)
Online Skin-Electrode Contact Quality Monitoring in Wearable Devices: An EEG Application.
In: 2022 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), 2022-5-16 - 2022-5-19, Ottawa, Canada.
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I2MTC 2022 - Online skin-electrode contact quality monitoring in wearable devices - An EEG application.pdf - Author Accepted Manuscript Download (472kB) | Preview |
Abstract
Wearable devices are becoming increasingly promising for many applications, but the accuracy of their measurements relies on good skin-electrode contact quality throughout the recording. While it is possible to assess the contact quality before the recording by measuring the impedance between electrodes, an accurate and reliable tool to monitor the contact quality during the recording is still unavailable. This is especially important for EEG recordings, because of the very low signal-to-noise ratio of EEG signals. This paper proposes an innovative approach for continuous monitoring of the skin-electrode contact quality, based on the measurement of the line-frequency radiated interference, always present in indoor environments. Differently from other existing methods that measure the absolute interference power, the proposed method uses the relative 50 Hz power normalized to a reference channel, to detect contact variations in individual channels that may occur during the recording, due to possible electrode displacement, gel dehydration or variations in contact pressure. The proposed method has been tested on a commercial wearable EEG device and shows some advantages compared to the signal quality index calculated by the device, in terms of sensitivity to small impedance differences and robustness in presence of muscular artifacts and environmental changes in the source of interference.
| Item Type: | Conference or Workshop Item (Unspecified) |
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| Uncontrolled Keywords: | Wearable sensors, Biomedical measurement, Biomedical monitoring, Biomedical electrodes, Bioimpedance, Electroencephalography |
| Divisions: | Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 25 Apr 2022 13:36 |
| Last Modified: | 15 Mar 2024 01:27 |
| DOI: | 10.1109/I2MTC48687.2022.9806519 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3153893 |
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