Seer Medical is a research-driven medical technology company with a mission to empower people to take better control of their health.
Research Review is a series where we pull apart peer-reviewed journal articles published by Seer Medical’s research team. Seer is proudly the home of some of the most brilliant minds advancing research in the world of epilepsy to develop innovative health management tools such as our Risk feature. The Risk feature will be available on the Seer app and allows people living with epilepsy to know when a seizure is most or least likely to occur.
Dr Pip Karoly is senior researcher at Seer whose doctorate first identified the seizure cycles used in our forecasting technology to provide Seer’s Risk feature. Pip sat down with us to explore “Multi-day cycles of heart rate are associated with seizure likelihood”, an article published in EBioMedicine.
The article is an observational cohort study where cardiac signals and seizures were monitored using long-term mobile seizure diaries and Fitbit smartwatches. These two datasets offered complementary information that provided the data used to identify multi-day heart cycles and the link between these cycles and seizure timing. These findings can be used to guide epilepsy therapy and seizure forecasting systems.
This Research Review details:
- What this article is about.
- How heart rate cycles affect people with epilepsy and how that can be used to improve seizure risk forecasting.
- How this could be useful for SUDEP research.
- Our next steps aimed at how to best present seizure risk information to people living with epilepsy.
- A path to wearable seizure forecasting.
- New questions for the research community, what other physiological systems might long-term heart rhythms affect?
Hi, I’m Pip Karoly. I’m a Data Scientist at Seer and a Senior Research Fellow at the University of Melbourne.
What is the article about?
This article presents a study where we used Fitbit smartwatches and the Seer app to capture seizure times, and we were able to link for the first time these individual long-term rhythms in people’s heart rate to their seizure timing or their seizure cycles.
How do heart rate cycles affect people with epilepsy?
Everybody in our cohort had some kind of longer heart rate cycle. A common rhythm was sort of weekly but not exactly seven days, between five and nine days, and also around a monthly rhythm, and this was true for men and women, and what we were able to see was that if you track the cycle, seizure times occur, or seizures were more likely at particular times in the cycle. So, maybe as it was just nearing the peak, or maybe as it was just nearing the trough of a cycle. So, seizures weren’t always happening at those times but they were much more likely, and that’s how we incorporate the information into forecasts.
Tell us about the relationship between the brain and the heart.
It’s currently not clear how these heart rate cycles are linked to seizure cycles or cycles in the brain. What we do know is that we found similar heart rate cycles in people without epilepsy, so that is really interesting and it suggests that longer term rhythms might be something that is much more widespread, it’s going on in everyone, and in people with epilepsy it just happens to influence their seizure timing, and we can use that.
What is the impact for sudden unexpected death in epilepsy (SUDEP) research?
Sudden unexpected death in epilepsy, or SUDEP, is a major problem facing people with seizures and earlier research has linked SUDEP potentially to changes in heart rate or breathing. So, these new findings are new findings showing that there are long term or slow rhythms in heart rate changes that are linked to seizure occurrence, could potentially also be translated to times when people are at higher risk of SUDEP and may need more monitoring.
Does this study impact the Seer app?
We’re currently piloting a seizure Risk feature in the Seer app, and we’ll be incorporating the heart rate cycles that we record from the Fitbit, and our primary consideration now is what is the most useful way of delivering a forecast for people? How can we best present this information about their risk cycles to them? and that is the most critical question in actually making our research useful to people with epilepsy.
What are the main takeaways from the study?
There are two main takeaway messages from this research. The first is for people with epilepsy in that these findings provide a really promising avenue for wearable seizure forecasting, but the second message is really for our basic scientific understanding of physiological rhythms in health and disease, and I think a massive unanswered question now for the research community is what are these long-term cycles that are affecting heart rate, that are affecting the brain, it’s not just people with epilepsy. So, what other areas might be influenced by long-term rhythms, potentially cardiovascular disease, potentially diabetes. And there’s a whole range of fields, and I think the research that might be generated from this study is very exciting.