Biomedical Engineering - Theses

Permanent URI for this collection

http://hdl.handle.net/11343/366

Filters

2018 - 2019 1 2020 - 2023 1
2
Reset filters

Settings
Statistics
Citations
Subject: epilepsy × Subject: forecasting ×

Search Results

Now showing 1 - 2 of 2
  • Item
    Thumbnail Image
    Cycles and Seizure Forecasting in Epilepsy
    Stirling, Rachel Elizabeth ( 2023-08)
    People with epilepsy were once termed “lunatics” because their seizures appeared to occur in synchrony with the lunar cycle. The cause was sinning at the wrong time of the lunar phase: “If they [the planets] should scrutinize while the Moon is putting an end to a certain phase, they produce maniacs, ecstatics, epileptics, those who chant”. This conviction was consistent with medicine at the time, which believed that the moon caused an unnaturally moist brain, leading to epileptic seizures. Nowadays, we know that most people with epilepsy have at least one seizure cycle, the periods of which are unique to the individual (7 days, 10 days, 20 days, 28 days, etc.). Yet we have a very limited understanding of where they derive from and how to best understand them for seizure forecasting and other applications. This thesis aims to expand our scientific understanding of the co-existing factors and mechanistic drivers of multiday cyclical patterns in epilepsy while investigating their utility in improving the performance of seizure forecasting algorithms. The presented research addresses this overarching aim by answering three questions: (1) What physiological signals correlate with cyclical patterns in epileptic seizures? (2) Can physiological signals correlating with cyclical patterns in epileptic seizures be tracked and utilised to improve seizure forecasting algorithms? (3) How can we begin investigating the systemic mechanisms of cycles in epilepsy and beyond? By answering these questions, this thesis aspires to give future researchers the foundational knowledge and resources needed to gain greater insight into cycles in epilepsy and mammalian biology.
  • Item
    Thumbnail Image
    Epileptic seizures: mechanisms and forecasting
    Karoly, Philippa Jane ( 2018)
    Seizure forecasting, like weather forecasting, was once considered the domain of charlatans and purveyors of science fiction. However, neuroscience has now advanced to the point of translating seizure forecasting research into widely available clinical applications. Just like weather apps that report the probability of rain on a given day, it is now conceivable that devices will inform people with epilepsy about their current likelihood of having a seizure. This information could be life-changing: restoring a sense of control and the ability to participate in everyday activities. Over 65 million people around the world have epilepsy; one third cannot control their seizures with medication. The unpredictability of seizures can be devastating, leading to persistent anxiety, exclusion from day-to-day life, serious injury or death. The aim of this thesis is to develop a clinically useful framework for forecasting seizures. The presented research addresses several key questions towards this goal: What drives seizure transitions? Are there underlying rhythms governing seizure onset? If underlying rhythms exist, how can they be integrated into a single determination of an individual's seizure likelihood? By presenting answers to these questions this thesis aims to form the basis for an innovative approach to seizure forecasting.