TY - JOUR
T1 - Medical technology
T2 - A systematic review on medical devices utilized for epilepsy prediction and management
AU - Ong, Jen Sze
AU - Wong, Shuet Nee
AU - Arulsamy, Alina
AU - Watterson, Jessica L.
AU - Shaikh, Mohd. Farooq
N1 - Funding Information:
This project is funded by Monash University Malaysia NEED (NEtwork for Equity through Digital Health) Grant Scheme 2020 (MED/NEED/11-2020/002).
Publisher Copyright:
© 2022 Bentham Science Publishers.
PY - 2022/5
Y1 - 2022/5
N2 - Background: Epilepsy is a devastating neurological disorder that affects nearly 70 million people worldwide. Epilepsy causes uncontrollable, unprovoked and unpredictable seizures that reduce the quality of life of those afflicted, with 1-9 epileptic patient deaths per 1000 patients occurring annu-ally due to sudden unexpected death in epilepsy (SUDEP). Predicting the onset of seizures and manag-ing them may help patients from harming themselves and may improve their well-being. For a long time, electroencephalography (EEG) devices have been the mainstay for seizure detection and monitor-ing. This systematic review aimed to elucidate and critically evaluate the latest advancements in medical devices, besides EEG, that have been proposed for the management and prediction of epileptic sei-zures. A literature search was performed on three databases, PubMed, Scopus and EMBASE. Methods: Following title/abstract screening by two independent reviewers, 27 articles were selected for critical analysis in this review. Results: These articles revealed ambulatory, non-invasive and wearable medical devices, such as the in-ear EEG devices; the accelerometer-based devices and the subcutaneous implanted EEG devices might be more acceptable than traditional EEG systems. In addition, extracerebral signal-based devices may be more efficient than EEG-based systems, especially when combined with an intervention trigger. Although further studies may still be required to improve and validate these proposed systems before commercialization, these findings may give hope to epileptic patients, par-ticularly those with refractory epilepsy, to predict and manage their seizures. Conclusion: The use of medical devices for epilepsy may improve patients' independence and quality of life and possibly prevent sudden unexpected death in epilepsy (SUDEP).
AB - Background: Epilepsy is a devastating neurological disorder that affects nearly 70 million people worldwide. Epilepsy causes uncontrollable, unprovoked and unpredictable seizures that reduce the quality of life of those afflicted, with 1-9 epileptic patient deaths per 1000 patients occurring annu-ally due to sudden unexpected death in epilepsy (SUDEP). Predicting the onset of seizures and manag-ing them may help patients from harming themselves and may improve their well-being. For a long time, electroencephalography (EEG) devices have been the mainstay for seizure detection and monitor-ing. This systematic review aimed to elucidate and critically evaluate the latest advancements in medical devices, besides EEG, that have been proposed for the management and prediction of epileptic sei-zures. A literature search was performed on three databases, PubMed, Scopus and EMBASE. Methods: Following title/abstract screening by two independent reviewers, 27 articles were selected for critical analysis in this review. Results: These articles revealed ambulatory, non-invasive and wearable medical devices, such as the in-ear EEG devices; the accelerometer-based devices and the subcutaneous implanted EEG devices might be more acceptable than traditional EEG systems. In addition, extracerebral signal-based devices may be more efficient than EEG-based systems, especially when combined with an intervention trigger. Although further studies may still be required to improve and validate these proposed systems before commercialization, these findings may give hope to epileptic patients, par-ticularly those with refractory epilepsy, to predict and manage their seizures. Conclusion: The use of medical devices for epilepsy may improve patients' independence and quality of life and possibly prevent sudden unexpected death in epilepsy (SUDEP).
KW - Electroencephalography
KW - electrophysiology device
KW - extracerebral signals
KW - seizure prediction
KW - SUDEP
KW - wearable device
UR - http://www.scopus.com/inward/record.url?scp=85129578560&partnerID=8YFLogxK
U2 - 10.2174/1570159X19666211108153001
DO - 10.2174/1570159X19666211108153001
M3 - Review Article
C2 - 34749622
AN - SCOPUS:85129578560
VL - 20
SP - 950
EP - 964
JO - Current Neuropharmacology
JF - Current Neuropharmacology
SN - 1570-159X
IS - 5
ER -