TY - GEN
T1 - An IoT Based Epilepsy Monitoring Model
AU - McHale, S. A.
AU - Pereira, E.
N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2021/7/16
Y1 - 2021/7/16
N2 - The emerging approach of personalised healthcare is known to be facilitated by the Internet of Things (IoT) and sensor-based IoT devices are in popular demand for healthcare providers due to the constant need for patient monitoring. In epilepsy, the most common and complex patients to deal with correspond to those with multiple strands of epilepsy, it is these patients that require long term monitoring assistance. These extremely varied kind of patients should be monitored precisely according to their key symptoms, hence specific characteristics of each patient should be identified, and medical treatment tailored accordingly. Consequently, paradigms are needed to personalise the information being defined by the condition of these patients each with their very individual signs and symptoms of epilepsy. Therefore, by focusing upon personalised parameters that make epilepsy patients distinct from each other this paper proposes an IoT based Epilepsy monitoring model that endorses a more accurate and refined way of remotely monitoring and managing the ‘individual’ patient.
AB - The emerging approach of personalised healthcare is known to be facilitated by the Internet of Things (IoT) and sensor-based IoT devices are in popular demand for healthcare providers due to the constant need for patient monitoring. In epilepsy, the most common and complex patients to deal with correspond to those with multiple strands of epilepsy, it is these patients that require long term monitoring assistance. These extremely varied kind of patients should be monitored precisely according to their key symptoms, hence specific characteristics of each patient should be identified, and medical treatment tailored accordingly. Consequently, paradigms are needed to personalise the information being defined by the condition of these patients each with their very individual signs and symptoms of epilepsy. Therefore, by focusing upon personalised parameters that make epilepsy patients distinct from each other this paper proposes an IoT based Epilepsy monitoring model that endorses a more accurate and refined way of remotely monitoring and managing the ‘individual’ patient.
KW - Healthcare
KW - IoT
KW - Personalisation
UR - http://www.scopus.com/inward/record.url?scp=85112722856&partnerID=8YFLogxK
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U2 - 10.1007/978-3-030-80129-8_15
DO - 10.1007/978-3-030-80129-8_15
M3 - Conference proceeding (ISBN)
AN - SCOPUS:85112722856
SN - 9783030801281
T3 - Lecture Notes in Networks and Systems
SP - 192
EP - 207
BT - Intelligent Computing - Proceedings of the 2021 Computing Conference
A2 - Arai, Kohei
PB - Springer Science and Business Media Deutschland GmbH
T2 - Computing Conference, 2021
Y2 - 15 July 2021 through 16 July 2021
ER -