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Univ.-Prof. Dr.-Ing. Horst-Michael Groß

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INHALTE

ROREAS

Overview

Title: Interaktiver RObotischer REha-ASsistent für das Lauf- und Orientierungstraining von Patienten nach Schlaganfällen
Duration:01.07.2013 - 31.03.2016
Funding:BMBF - Bundesministerium für Bildung und Forschung
Project Partner:MetraLabs GmbH, Ilmenau
m&i-Klinikgruppe Enzensberg (weiterführende Neurorehabilitation m&i-Fachklinik Bad Liebenstein)
SIBIS Inst. für Sozialforschung & Projektberatung GmbH, Berlin
Barmer GEK, Wuppertal (assoziierter Partner)

Project Manager:Prof. Dr. Horst-Michael Groß
Staff:

Dr.-Ing. Andrea Scheidig
Dipl.-Inf. Markus Eisenbach
Thanh Quang Trinh, MSc
Tim Wengefeld, MSc

Project Homepagewww.roreas.org
Preceding Projects:

Description

 About 2-5% of all health related costs in the western developed nations originate from stroke disease patterns. Due to demographic change, the rate of stroke occurrences is expected to increase, while at the same time family structures are changing and cohabitation of different generations, providing possibilities for informal care, is receding. In effect, demand for rehabilitative follow-up care for stroke patients is increasing.
A new trend in rehabilitation care, promising vast medical as well as economic potential, is so-called Self Training.

ROREAS aims to develop  a robotic rehabilitation assistant for walking and orientation exercising in self training during clinical stroke follow-up care. The robotic rehab assistant accompanies inpatients during walking exercises, practicing both mobility and spatial orientation skills.  It shall also address patients’ insecurity and anxiety (“Am I able to do that”, “Will I find my way back?”) which are possible reasons for failing self training.
The assistant also monitors the exercises and stores clinical records  for accounting and clearing with insurance funds, thus combining improved training capabilities for patients and organizational efficiency for the care or treatment facility.

The project requires consistent integration of robust autonomous navigation in public environments, advanced reliable human-machine-interaction and intuitive assistive functions allowing customized individual exercise plans. Beside the development of the robotic assistant, detailed analysis shall quantify its medical effectiveness and reveal factors promoting or impeding the acceptance of its application.