Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Shivaraja, Theeban Raj, Remli, Rabani, Kamal, Noorfazila, Wan Zaidi, Wan Asyraf, Chellappan, Kalaivani
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
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
_version_ 1785024890531741696
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
work_keys_str_mv AT shivarajatheebanraj assessmentofa16channelambulatorydryelectrodeeegforremotemonitoring
AT remlirabani assessmentofa16channelambulatorydryelectrodeeegforremotemonitoring
AT kamalnoorfazila assessmentofa16channelambulatorydryelectrodeeegforremotemonitoring
AT wanzaidiwanasyraf assessmentofa16channelambulatorydryelectrodeeegforremotemonitoring
AT chellappankalaivani assessmentofa16channelambulatorydryelectrodeeegforremotemonitoring