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ESPS

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Epileptic Seizure Prediction System ESPS Predicting and preventing epileptic...

Epileptic Seizure Prediction System ESPS Predicting and preventing epileptic seizures based on respiratory biofeedback machine learning. Epilepsy is one of the most common nervous system disorders and affects more than 50M people worldwide. The majority of new-onset cases occur in elderly and children. Currently there is no cure for epilepsy. Although antiepileptic... ver más

31/12/2019

iBreve Ltd

71K€

Presupuesto del proyecto: 71K€

Líder del proyecto

IBREVE LIMITED No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Ver 5 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2019-12-31

EIC-SMEInst-2018-2020: SME instrument

I+D

Cerrada hace 7 años

0% 70% 100%

Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

5 Participantes

iBreve Ltd

50.00K€ | Lider

AERNNOVA ENGINEERING DIVISIO...

807.21K€ | Participante

COMPASS INGENIERIA Y SISTEMA...

184.59K€ | Participante

ESI GROUP HISPANIA

674.26K€ | Participante

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Duración del proyecto: 5 meses Fecha Inicio: 2019-07-21
Fecha Fin: 2019-12-31

Líder del proyecto

IBREVE LIMITED No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 71K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Epilepsy is one of the most common nervous system disorders and affects more than 50M people worldwide. The majority of new-onset cases occur in elderly and children. Currently there is no cure for epilepsy. Although antiepileptic drugs can help, one third of all patients do not respond to any pharmacological intervention. This staggering number has not changed in decades, despite over 14 new therapies entering the market. The unpredictable nature of seizures causes the largest burden for patients as it literally disrupts their lives. Patients with several seizures a week are hesitant to leave the house & find it hard to obtain employment. Reliably predicting seizures enables an independent life for the patient and at the same time reduces healthcare costs caused by clinician visits, injuries & caretaking. iBreve’s new patent-pending wearable technology analyzes respiratory patterns in real-time, enabling market applications for seizure prediction, respiratory treatment & stress management. iBreve’s technology received interest from Harvard’s Boston Children’s Hospital to be included in clinical trials for seizure detection & prediction. The ESPS machine learning algorithm calculates seizure probability & intensity and if desired an alert is sent to the patient’s caregiver. The tracking and analysis of seizures can be shared with clinicians & allows to personalize treatment. Main objective of this feasibility study is the development of a comprehensive business plan to evaluate the opportunities & risks of introducing ESPS into the homecare market. All project activities follow the Healthcare Innovation Cycle methodology & are structured around 4 development pillars - Technology, Market & Business, Clinical and Regulatory. The introduction of ESPS is prone to disrupt the epilepsy market by reducing treatment costs per patient by up to 70%. Thus, saving 14B€ in health care costs in Europe alone and creating a major shift towards preventive & personalized treatment.

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