Capturing markers of seizure-modulation using long-term EEG and wearable sensors (Computational Neurology)

The symptoms and severity of epileptic seizures can change from one seizure to the next within the same patient. Our recent publication (Schroeder et al. 2020, PNAS) showed that these changes are not random, but rather change according to circadian or longer-term rhythms. In parallel, recent work has also shown that seizure likelihood often follows daily, monthly, and/or seasonal rhythms. These rhythms are also possibly connected with other physiological fluctuations such as respiration and heart rate and influenced by environmental factors like air temperature and pressure. Together, the current evidence suggests that we should be able to predict the periods of time, when seizures are likely to be more severe.

As wearable technology and subcutaneous implants become more accessible, physiological signals and EEG can be continuously recorded over a long period of time. We propose to find and track markers of seizure modulation using wearable devices, combined with long-term EEG and environmental sensor data.

Skills and training

The student will be embedded in the CNNP Lab (www.cnnp-lab.com), which offers a vibrant environment for interdisciplinary neurological research. After getting familiar with existing data and analyses, the student will have the choice to focus on analytical (data science) aspects of the project or establish prospective collection of wearable data in the epilepsy monitoring unit. This student will be invited to spend 3+ months at UNEEG with their data analytics lab and working alongside experts in wearable technology. The student should complete their PhD with skills in both advanced data analytics, wearable data acquisition, and have an insight into an exciting med-tech domain.

How to Apply:

Applications should be made by emailing [Email Address Removed] with:

• a CV (including contact details of at least two academic (or other relevant) referees);
• A covering letter – clearly stating your first-choice project, and optionally 2nd and 3rd ranked projects, as well as including whatever additional information you feel is pertinent to your application; you may wish to indicate, for example, why you are particularly interested in the selected project(s);
• copies of your relevant undergraduate degree transcripts and certificates;
• a copy of your passport (photo page).

A GUIDE TO THE FORMAT REQUIRED FOR THE APPLICATION DOCUMENTS IS AVAILABLE AT http://www.cando.ac.uk/eruk-phd/ . Applications not meeting these criteria may be rejected.

In addition to the above items, please email a completed copy of the Application Form (as a Word document) to [Email Address Removed]  A blank copy of this form can be found at: http://www.cando.ac.uk/eruk-phd/

Informal enquiries may be made to [Email Address Removed]. The closing date for applications is 31st March 2022 at 5.00pm (UK time).