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Assessment of a 16-Channel Ambulatory Dry Electrode EEG for Remote Monitoring
Ambulatory EEGs began emerging in the healthcare industry over the years, setting a new norm for long-term monitoring services. The present devices in the market are neither meant for remote monitoring due to their technical complexity nor for meeting clinical setting needs in epilepsy patient monit...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10098757/ https://www.ncbi.nlm.nih.gov/pubmed/37050713 http://dx.doi.org/10.3390/s23073654 |
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author | Shivaraja, Theeban Raj Remli, Rabani Kamal, Noorfazila Wan Zaidi, Wan Asyraf Chellappan, Kalaivani |
author_facet | Shivaraja, Theeban Raj Remli, Rabani Kamal, Noorfazila Wan Zaidi, Wan Asyraf Chellappan, Kalaivani |
author_sort | Shivaraja, Theeban Raj |
collection | PubMed |
description | Ambulatory EEGs began emerging in the healthcare industry over the years, setting a new norm for long-term monitoring services. The present devices in the market are neither meant for remote monitoring due to their technical complexity nor for meeting clinical setting needs in epilepsy patient monitoring. In this paper, we propose an ambulatory EEG device, OptiEEG, that has low setup complexity, for the remote EEG monitoring of epilepsy patients. OptiEEG’s signal quality was compared with a gold standard clinical device, Natus. The experiment between OptiEEG and Natus included three different tests: eye open/close (EOC); hyperventilation (HV); and photic stimulation (PS). Statistical and wavelet analysis of retrieved data were presented when evaluating the performance of OptiEEG. The SNR and PSNR of OptiEEG were slightly lower than Natus, but within an acceptable bound. The standard deviations of MSE for both devices were almost in a similar range for the three tests. The frequency band energy analysis is consistent between the two devices. A rhythmic slowdown of theta and delta was observed in HV, whereas photic driving was observed during PS in both devices. The results validated the performance of OptiEEG as an acceptable EEG device for remote monitoring away from clinical environments. |
format | Online Article Text |
id | pubmed-10098757 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100987572023-04-14 Assessment of a 16-Channel Ambulatory Dry Electrode EEG for Remote Monitoring Shivaraja, Theeban Raj Remli, Rabani Kamal, Noorfazila Wan Zaidi, Wan Asyraf Chellappan, Kalaivani Sensors (Basel) Article Ambulatory EEGs began emerging in the healthcare industry over the years, setting a new norm for long-term monitoring services. The present devices in the market are neither meant for remote monitoring due to their technical complexity nor for meeting clinical setting needs in epilepsy patient monitoring. In this paper, we propose an ambulatory EEG device, OptiEEG, that has low setup complexity, for the remote EEG monitoring of epilepsy patients. OptiEEG’s signal quality was compared with a gold standard clinical device, Natus. The experiment between OptiEEG and Natus included three different tests: eye open/close (EOC); hyperventilation (HV); and photic stimulation (PS). Statistical and wavelet analysis of retrieved data were presented when evaluating the performance of OptiEEG. The SNR and PSNR of OptiEEG were slightly lower than Natus, but within an acceptable bound. The standard deviations of MSE for both devices were almost in a similar range for the three tests. The frequency band energy analysis is consistent between the two devices. A rhythmic slowdown of theta and delta was observed in HV, whereas photic driving was observed during PS in both devices. The results validated the performance of OptiEEG as an acceptable EEG device for remote monitoring away from clinical environments. MDPI 2023-03-31 /pmc/articles/PMC10098757/ /pubmed/37050713 http://dx.doi.org/10.3390/s23073654 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Shivaraja, Theeban Raj Remli, Rabani Kamal, Noorfazila Wan Zaidi, Wan Asyraf Chellappan, Kalaivani Assessment of a 16-Channel Ambulatory Dry Electrode EEG for Remote Monitoring |
title | Assessment of a 16-Channel Ambulatory Dry Electrode EEG for Remote Monitoring |
title_full | Assessment of a 16-Channel Ambulatory Dry Electrode EEG for Remote Monitoring |
title_fullStr | Assessment of a 16-Channel Ambulatory Dry Electrode EEG for Remote Monitoring |
title_full_unstemmed | Assessment of a 16-Channel Ambulatory Dry Electrode EEG for Remote Monitoring |
title_short | Assessment of a 16-Channel Ambulatory Dry Electrode EEG for Remote Monitoring |
title_sort | assessment of a 16-channel ambulatory dry electrode eeg for remote monitoring |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10098757/ https://www.ncbi.nlm.nih.gov/pubmed/37050713 http://dx.doi.org/10.3390/s23073654 |
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