TY - GEN
T1 - Implementation of wireless biosensor for continuous EEG monitoring in neurological intensive care
AU - Hsu, Tien Yu
AU - Kuo, Terry B.J.
AU - Lin, Ming Chin
N1 - Publisher Copyright:
© 2020 European Federation for Medical Informatics (EFMI) and IOS Press.
PY - 2020/6/16
Y1 - 2020/6/16
N2 - Seizure is a common complication in a neurological intensive care unit (NICU) and it requires continuous electroencephalograms (EEG) monitoring. Implementation of EEG for each bed in a NICU is very expensive and require labor work for interpretation of EEG. To provide an affordable device of EEG in NICU, we developed a low-cost wireless biosensor, which utilized the current standard of the internet of things technology (IoT). In this study, we implement a wireless biosensor for continuous EEG monitoring in NICU and discuss its feasibility. To provide a low-cost EEG device, we embraced Bluetooth and mobile phone technology, which is convenient for implementation. We build a two-channel EEG biosensor, which utilizes Bluetooth to transmit the signal to mobile phones. Then, mobile phones use Wi-Fi technology to send data to the server. Additionally, we also developed a registry to organize the patient's EEG data. In six months research period, we have 65.8% of patients collected successfully. Using 2 channel-biosensor in NCU is feasible. It also develops a neuromedical database by collecting and monitoring physiological signals to develop future neuromedical research.
AB - Seizure is a common complication in a neurological intensive care unit (NICU) and it requires continuous electroencephalograms (EEG) monitoring. Implementation of EEG for each bed in a NICU is very expensive and require labor work for interpretation of EEG. To provide an affordable device of EEG in NICU, we developed a low-cost wireless biosensor, which utilized the current standard of the internet of things technology (IoT). In this study, we implement a wireless biosensor for continuous EEG monitoring in NICU and discuss its feasibility. To provide a low-cost EEG device, we embraced Bluetooth and mobile phone technology, which is convenient for implementation. We build a two-channel EEG biosensor, which utilizes Bluetooth to transmit the signal to mobile phones. Then, mobile phones use Wi-Fi technology to send data to the server. Additionally, we also developed a registry to organize the patient's EEG data. In six months research period, we have 65.8% of patients collected successfully. Using 2 channel-biosensor in NCU is feasible. It also develops a neuromedical database by collecting and monitoring physiological signals to develop future neuromedical research.
KW - Continuous EEG
KW - Neurointensive care unit
KW - Two-channel biosensor
KW - Wearable device
UR - http://www.scopus.com/inward/record.url?scp=85086886323&partnerID=8YFLogxK
U2 - 10.3233/SHTI200420
DO - 10.3233/SHTI200420
M3 - Conference contribution
C2 - 32570637
AN - SCOPUS:85086886323
T3 - Studies in Health Technology and Informatics
SP - 1317
EP - 1318
BT - Digital Personalized Health and Medicine - Proceedings of MIE 2020
A2 - Pape-Haugaard, Louise B.
A2 - Lovis, Christian
A2 - Madsen, Inge Cort
A2 - Weber, Patrick
A2 - Nielsen, Per Hostrup
A2 - Scott, Philip
PB - IOS Press
T2 - 30th Medical Informatics Europe Conference, MIE 2020
Y2 - 28 April 2020 through 1 May 2020
ER -