Abstract
The premises made in this paper put the future of personalisation in epilepsy into focus, a focus that shifts from a one-size fits all to a focus on the core of the epilepsy patients’ individual characteristics. 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. These extremely varied kind of patients should be monitored precisely according to their identified key symptoms and specific characteristics then treatment tailored accordingly. Consequently, paradigms are needed to personalise this information. By focusing upon personalised parameters that make epilepsy patients distinct this paper proposes an IoT based Epilepsy monitoring model endorsing a more accurate and refined way of remotely monitoring the ‘individual’ patient.
Highlights
By integrating Internet of Things (IoT) sensor-based devices deployed remotely and personalised patient data into a combined monitoring framework a vision of personalisation is realised
This study revealed some irrefutable evidence derived from patient profile analysis and experimental data that seizure detection using sensors positioned on different parts of a patents body makes an impact on the monitoring of epilepsy, endorsing that modern computer science is providing a timely chance for a more personalised approach to the monitoring and management of epilepsy
As discovered during a review to select the best sensor for each individual patient there was limited data on which was the best sensor for each seizure type, this was unfortunate despite an internationally active research effort, signifying the gap in knowledge, again, for understanding the individual epilepsy patient [16]
Summary
By integrating IoT sensor-based devices deployed remotely and personalised patient data into a combined monitoring framework a vision of personalisation is realised. This study revealed some irrefutable evidence derived from patient profile analysis and experimental data that seizure detection using sensors positioned on different parts of a patents body makes an impact on the monitoring of epilepsy, endorsing that modern computer science is providing a timely chance for a more personalised approach to the monitoring and management of epilepsy.
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