Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2017 Dec 27;4(6):ENEURO.0349-17.2017.
doi: 10.1523/ENEURO.0349-17.2017. eCollection 2017 Nov-Dec.

Seizure Forecasting from Idea to Reality. Outcomes of the My Seizure Gauge Epilepsy Innovation Institute Workshop

Affiliations

Seizure Forecasting from Idea to Reality. Outcomes of the My Seizure Gauge Epilepsy Innovation Institute Workshop

Sonya B Dumanis et al. eNeuro. .

Abstract

The Epilepsy Innovation Institute (Ei2) is a new research program of the Epilepsy Foundation designed to be an innovation incubator for epilepsy. Ei2 research areas are selected based on community surveys that ask people impacted by epilepsy what they would like researchers to focus on. In their 2016 survey, unpredictability was selected as a top issue regardless of seizure frequency or severity. In response to this need, Ei2 launched the My Seizure Gauge challenge, with the end goal of creating a personalized seizure advisory system device. Prior to moving forward, Ei2 convened a diverse group of stakeholders from people impacted by epilepsy and clinicians, to device developers and data scientists, to basic science researchers and regulators, for a state of the science assessment on seizure forecasting. From the discussions, it was clear that we are at an exciting crossroads. With the advances in bioengineering, we can utilize digital markers, wearables, and biosensors as parameters for a seizure-forecasting algorithm. There are also over a thousand individuals who have been implanted with ambulatory intracranial EEG recording devices. Pairing up peripheral measurements to brain states could identify new relationships and insights. Another key component is the heterogeneity of the relationships indicating that pooling findings across groups is suboptimal, and that data collection will need to be done on longer time scales to allow for individualization of potential seizure-forecasting algorithms.

Keywords: algorithm; data collection; epilepsy; multimodal input; seizure forecasting; temporal pattern.

PubMed Disclaimer

References

    1. Bandodkar AJ, Wang J (2014) Non-invasive wearable electrochemical sensors: a review. Trends Biotechnol 32:363–371. 10.1016/j.tibtech.2014.04.005 - DOI - PubMed
    1. Baud MO, Kleen JK, Mirro EA, Andrechak JC, King-Stephans D, Chang EF, Rao VR (in press) Multi-day rhythms modulate seizure risk in epilepsy. Nat Commun - PMC - PubMed
    1. Bercel NA (2006) The periodic features of some seizure states. Ann NY Acad Sci 117:555–562. 10.1111/j.1749-6632.1964.tb48206.x - DOI - PubMed
    1. Berg AT, Millichap JJ (2013) The 2010 revised classification of seizures and epilepsy. Continuum (Minneap Minn) 19 [3 Epilepsy]:571–597. 10.1212/01.CON.0000431377.44312.9e - DOI - PMC - PubMed
    1. Brodie MJ, Barry SJE, Bamagous GA, Norrie JD, Kwan P (2012) Patterns of treatment response in newly diagnosed epilepsy. Neurology 78:1548–1554. 10.1212/WNL.0b013e3182563b19 - DOI - PMC - PubMed

Publication types