One percent of the population worldwide has epilepsy (Fiest, et al., 2017). EEG is the most important diagnostic tool for patients with seizures and suspected epilepsy. However, it is unavailable to the majority of the global population because the equipment is expensive (in the order of tens of thousands of Euros) and expertise for data-capture and interpretation is lacking (Mehndiratta & Wadhai, 2015). Around 80% of people with epilepsy live in resource-poor countries (Leonardi & Ustun, 2002), and around 75% are not treated (Meyer, Dua, Ma, Saxena, & Birbeck, 2010). The World Health Organization (WHO) estimates that up to 70% of these people live seizure free life if properly diagnosed and treated (Smith, 2005; WHO, 2019). To bridge this diagnostic and treatment gap and improve the quality of care for most of the world’s inhabitants, the study team has developed an easy-to-use, portable, smartphone connected EEG device that uses a smart phone to facilitate data collection and remote interpretation. This intervention has been tested previously in Sub- Saharan Africa, specifically in the Republic of Guinea (Williams et al.., 2019). In this trial, we target non-expert medical workers at the Aga Khan University Hospital in Nairobi, specifically nurses as a user group. If this group is able to use our device to take high-quality EEG, then our device can effectively address a large portion of disease burden by separating data collection and interpretation.

Our solution will aim at clinical use for epilepsy diagnosis and the main innovation is delivering an EEG device that is usable by non-experts with minimal training paired with an EEG recording service, not only the EEG device. We will provide an easy-to-use and end-to- end solution for epilepsy diagnostic support. Our solution is aimed at the ~70% of epilepsy cases that can be diagnosed “easily” (Smith, 2005; WHO, 2019). Our recording system, the BrainCapture-1 (BC-1) consists of 4 parts: An electrode cap in 3 sizes, an amplifier, an app, and cloud storage. This intervention is an affordable solution that 1) allows nurses with minimal extra training to perform recordings at remote locations and 2) assists local doctors to make diagnosis and treatment decisions by providing an EEG report. To make this happen, the solution will be robust to all kinds of conditions, like weather and cultural difficulties in interpreting the user interface.