Seizure Forecasting Study

Empatica is running a first-of-its-kind study to develop a seizure forecasting algorithm using real-world data, collected with groundbreaking wearable technology. The study is open to all US users of the new, FDA-cleared Empatica EpiMonitor. This is your chance to be part of it.

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Being able to know when your next seizure is coming so you can plan your life feels like a distant scenario.

It shouldn’t be.

EpiMonitor is an all-in-one solution for people living with epilepsy, combining automated and manual seizure alerts with a seizure diary alongside sleep and activity tracking. It is the only FDA-cleared smartwatch solution for epilepsy in the US, for adults and children ages 6 and older.

Support what could be the biggest scientific breakthrough in epilepsy research

The study aims to develop a seizure forecasting algorithm for people living with epilepsy from the world’s largest real-world dataset. Participation is open to all US users of the Empatica EpiMonitor.

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Why is seizure forecasting important?

65 million people in the world are affected by epilepsy, and around one third of those live with seizures that cannot be controlled by medications. Seizures are disruptive health events and can have a significant negative impact on quality of life and increase risk of injury and death for people with epilepsy.

“Reliable seizure forecasts could potentially allow people living with recurrent seizures to modify their activities, take a fast-acting medication, or increase neuromodulation therapy to prevent or manage impending seizures.”1

Developing a reliable and accurate seizure forecasting algorithm has so far been a challenge for researchers due to one major reason: data volumes. 2 Large datasets are extremely important to train an algorithm to achieve an accurate prediction of when someone will have a seizure, but they are also extremely difficult to gather. With this study, Empatica seeks to overcome this challenge with the participation of its community.

1. https://www.nature.com/articles/s41598-021-01449-2 2. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8578354/
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How to participate

The study is open to US-based users of EpiMonitor, Empatica’s new, FDA-cleared epilepsy monitoring system. Participants can share their data and aid the development of a personalized prediction output. Eligible participants need to be aged 6 and up, based in the US, and have a diagnosis of or be at risk of epilepsy.

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What will the study entail?

  • Participants will be required to wear EmbracePlus as part of the EpiMonitor system
  • All data will be collected automatically and anonymously in the background
  • This data will include seizure data, pulse rate data, sleep data and movement-related data
  • Participants will be asked to fill in surveys regarding their medication intake and experience using EpiMonitor
  • Participants will need to keep a faithful seizure diary, correctly labeling seizures and false alerts
  • Participation is expected to last 6-15 months
  • Participants can withdraw at any time

*Please note that participation in the study may affect the battery performance of EmbracePlus.

Our seizure forecasting study in the press

Healthcare Technology Report

Empatica Advances Seizure Forecasting with Groundbreaking Real-World Data Study

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Medtech Dive

Empatica aims to develop seizure-forecasting algorithm based on wearable data

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Medical Device Network

Empatica launches clinical trial to predict refractory seizures with AI

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Feirce Biotech

Empatica plots wearable-based study to develop seizure prediction algorithm

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First word health tech:

Empatica launches study to develop seizure forecasting

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Seizure forecasting research using Empatica’s technology

Gregg, Nicholas M et al.

Seizure occurrence is linked to multiday cycles in diverse physiological signals

Nasseri, M., Pal Attia, T., Joseph, B. et al.

Ambulatory seizure forecasting with a wrist-worn device using long-short term memory deep learning

Meisel, Christian et al.

Machine learning from wristband sensor data for wearable, noninvasive seizure forecasting

Vieluf, Solveig et al.

Seizure-related differences in biosignal 24-h modulation patterns

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