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ReHyb SIGNED

Rehabilitation based on Hybrid neuroprosthesis

Total Cost €

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EC-Contrib. €

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Partnership

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 ReHyb project word cloud

Explore the words cloud of the ReHyb project. It provides you a very rough idea of what is the project "ReHyb" about.

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Project "ReHyb" data sheet

The following table provides information about the project.

Coordinator
TECHNISCHE UNIVERSITAET MUENCHEN 

Organization address
address: Arcisstrasse 21
city: MUENCHEN
postcode: 80333
website: www.tu-muenchen.de

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Germany [DE]
 Total cost 7˙153˙873 €
 EC max contribution 7˙153˙873 € (100%)
 Programme 1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
 Code Call H2020-ICT-2019-2
 Funding Scheme RIA
 Starting year 2020
 Duration (year-month-day) from 2020-01-01   to  2023-12-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    TECHNISCHE UNIVERSITAET MUENCHEN DE (MUENCHEN) coordinator 1˙079˙750.00
2    IUVO SRL IT (PONTEDERA) participant 974˙105.00
3    SCUOLA SUPERIORE DI STUDI UNIVERSITARI E DI PERFEZIONAMENTO S ANNA IT (PISA) participant 944˙843.00
4    DANMARKS TEKNISKE UNIVERSITET DK (KGS LYNGBY) participant 862˙985.00
5    IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE UK (LONDON) participant 679˙325.00
6    FUNDACIO INSTITUT DE BIOENGINYERIA DE CATALUNYA ES (BARCELONA) participant 589˙250.00
7    SCHON KLINIK BAD AIBLING GMBH & COKG DE (PRIEN) participant 517˙165.00
8    STELAR SECURITY TECHNOLOGY LAW RESEARCH UG DE (HAMBURG) participant 412˙700.00
9    CONGREGAZIONE DELLE SUORE INFERMIERE DELL ADDOLORATA IT (Como) participant 385˙625.00
10    Össur hf IS (Reykjavik) participant 363˙250.00
11    FUNDACION TECNALIA RESEARCH & INNOVATION ES (DERIO BIZKAIA) participant 344˙875.00

Map

 Project objective

Advancements in mechanical engineering and automation technologies have led to global expectations for robotic devices in rehabilitation to cope with a forecast of global ageing and shortage in clinical professionals in the near future. In particular, stroke patients often have to go through extensive rehabilitation or lose daily skills required for an independent self-determined life due to motor deficits. In contrast to classical physical therapists, robotic systems are able to tirelessly and precisely apply intense manual labour, while accurately measuring performance and improvements of the patient. Active exoskeletons meet these requirements and possess the additional advantage of non-stationary design that allows for flexible training and mobility of the patient. Preliminary studies indicate that the training efficiency can be improved if, in addition to the guidance by the exoskeleton, the users motor functions are actively controlled using functional electrical stimulation (FES). Such hybrid systems are advantageous because the users’ own muscular activity initialise the movements and are not passively guided through an external force. However, the required control which coordinates the active exoskeleton and stimulation for the human motor functions, especially in terms of dexterity skills necessary for activities of daily living, is more complex due to the unsolved questions on shared control and the missing models of the human motor function with respect to FES. Thus, the ReHyb project designs an upper-body hybrid neuroprosthesis using cooperative control strategies based on data-driven system identification and probabilistic estimation techniques for the internal human states, namely digital twin of a user. Our goal is a patient-specific, assist-as-needed device which maximises the training efficiency during home-based rehabilitation as means of serious gaming, and offers a pleasant user experience by supporting patients in daily life activities.

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The information about "REHYB" are provided by the European Opendata Portal: CORDIS opendata.

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