Project Explanation

Predicting Epileptic Seizures



Innovating, our project is going to improve the life of people with epilepsy

Epilepsy is the most common of serious brain diseases reaching over 60 million people around the world, from which 80% are in developing countries. Although there are medications and surgeries available, they do not have any effect in one third of the patients. These patientas would benefit from an early alarm of an incoming seizure.

To date, there is no device that is able to predict an incoming seizure.

Espistemic has a tested and proved software and is finalizing its implementation in a portable device.

This device will improve quality of life of people with epilepsy, opening doors for a more independent life without serious consequences and so they are able to count on the security of a faster medical response BEFORE a seizure happens. In addition to alerting the user, the device sends an alert to an application that can be installed in the user's caregiver's smartphone.

Image of children playing at the beach

If patients could learn that a seizure was coming beforehand, they could prepare themselves to diminish its effects. Our device, offers just that, thus helping people with epilepsy around the world to be able to perform activities that they currently cannot without risking theirs or other people’s lives.

Our schedule

Project's Timeline

Data Analysis

A seizure is easily identifiable in an electroencephalogram at the moment it happens:

Patient’s electroencephalogram signal while having an epileptic seizure
Patient's electroencephalogram signal while having an epileptic seizure

Our method consists in data processing based on non-linear dynamic systems that allows the seizure to be detected 25 minutes in advance on average.

The data analyzed in this project came from two different sources:

Data handling

Image of the graph with the data
  • The chart shows the result of our studies: the distribution of “alerts” in real signals of epileptic patients.
  • The chart shows only the FIRST alert generated for each patient.
  • We observed that the majority of these alerts occurred in a range of 15 to 35 minutes before the outbreak.


Epistemic News

Paula Gomez, founder of Epistemic wins the Cartier Women's Initiative Awards 2018

The newspaper Pequenas Empresas Grandes Negócios reported Paula's reception of the Cartier Women's Initiative Awards 2018.

Newspaper article on the award received by Paula Gomez featured in Pequenas Empresas Grandes Negócios

Epistemic on the Futura Channel

Check out Epistemic's Marketing Director's Interview at the Futura Channel on the show Conexão (Connection).

Video of the interview

Learn more about those behind the project

This is the result of a scientific research conducted for 7 years. The method has been perfected to the point where the seizures can be detected up to an average of 25 minutes in advance and was tested with signals from several different patients with epilepsy

For the development of this project, Epistemic brought together a highly qualified team. Learn more about them by clicking on the pictures below.

  • Hilda Cerdeira

    R&D Director and Partner and Co-founder

    Hilda Cerdeira

    PhD Physicist

    Professor at UNESP, Brazil

  • Paula Gomez

    CEO and Partner and Co-founder

    Paula Gomez

    PhD Electrical Engineering

    MBA - Insead

    Entrepreneur – Resp. for Business

  • Conrado de Vitor

    Partner and CTO

    Conrado de Vitor

    Electrical Engineer

    USP - University of São Paulo

  • Giuliano de Vitor

    Partner and CIO

    Giuliano de Vitor

    Computer Engineer

    Univ. São Francisco - Brazil

  • Dr. Renato Anghinah

    Medical Consultant

    Dr. Renato Anghinah

    PhD. Neurologist specialized in epilepsy

    Professor at UCL, London

  • Adriana Cerdeira

    Web Development

    Adriana Cerdeira

    Publicity and Advertisement - PUC-SP

  • Diogo Dias

    Sr. Firmware Developer / Master

    Diogo Dias

    Biomedical Engineer UFABC

  • Jorge Bianchetti Jr

    Hardware Developer

    Jorge Bianchetti Jr

    Control and Automation Engineering Student - UFABC

  • Marcelo Henrique da Silva


    Marcelo Henrique da Silva

    Production Engineering Student – FMU

  • João Victor Martins Reis

    Electronic Technitian

    João Victor Martins Reis

    Electric Engineering Student – UFABC

  • Edgar Tanaka

    Data Analysis Engineer

    Edgar Tanaka

    Computer Engineer

    UNICAMP - University of Campinas - Brazil

  • Rafael Buchner Kaihatu

    Software Engineer

    Rafael Buchner Kaihatu

    Computer Engineer

    UNICAMP - University of Campinas - Brazil

  • João Marcos Marques

    Big Data Analist

    João Marcos Marques

    Mechatronics Engineering Student at USP

  • Mateus Duarte

    Firmware Developer

    Mateus Duarte

    Electronics Engineering Student USP

  • Rafael Mosna


    Rafael Mosna

    Electrical Engineer

    USP - Brazil

  • Newton Bomeisel

    Lead Hardware Engineer

    Newton Bomeisel

    Newton- Electrical Engineer UNICAMP

  • Luan Miranda

    Mechanical Designer

    Luan Miranda

    Mechanical Engineering Student UFABC

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