Record #241417 - GSI Repository

EPINOSTICS

Artificial Intelligence powered epilepsy diagnostics

Grant period	2020-09-01 - 2022-08-31
Funding body	European Union
Call number	H2020-EIC-SMEInst-2018-2020-3
Grant number	960877
Identifier	G:(EU-Grant)960877

Note: 65 million people globally suffer from epilepsy. The neurological disease causes significant suffering to patients and their caregivers, and its costs in Europe exceed €13 billion annually. Although efficient medications are available, they do not work for 30% of the patients who keep suffering from seizures due to the shortcomings of current epilepsy diagnostics methods. Neurologists need detailed data about seizures to select the best treatment for each patient, but current methods do not provide that data. Neuro Events Labs is developing an accurate, scalable and affordable solution called ‘Aida’ for epileptic diagnostics, providing neurologists with a comprehensive visual overview of the patients’ seizures. The Aida platform is based on a set of proprietary, patent-pending deep learning algorithms and latest camera technologies. Using these disruptive technologies, Aida detects seizure type, severity and length with unprecedented accuracy and reliability. The Aida prototype has been piloted in clinical at the Tampere University Hospital to select the best treatment and improve the quality of life of epilepsy patients with outstanding results. Neuro Event Labs is a venture-backed Finnish SME with a growth-oriented energetic team with extensive experience in building and scaling successful high-tech businesses. Our competences range from business development & sales to 3D cameras, artificial intelligence and neurology. The EPINOSTICS project allows us to develop capabilities of automatics detection and classification of all motor seizure types and deliver important health benefits globally. The unprecedented functionality allows us to capture a significant portion of the €6.5 billion annual market opportunity. The market is eager for new technologies because the existing methods do not provide satisfactory results.

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Record created 2021-10-10, last modified 2023-03-01

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