AMYO
Advanced Myoelectric Control of Prosthetic Systems
| Coordinatore | OTTO BOCK HEALTHCARE GMBH
Organization address
address: MAX-NAEDER-STRASSE 15 contact info |
| Nazionalità Coordinatore | Germany [DE] |
| Totale costo | 1˙152˙406 € |
| EC contributo | 1˙152˙406 € |
| Programma | FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) |
| Code Call | FP7-PEOPLE-2009-IAPP |
| Funding Scheme | MC-IAPP |
| Anno di inizio | 2010 |
| Periodo (anno-mese-giorno) | 2010-09-01 - 2014-08-31 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
OTTO BOCK HEALTHCARE GMBH
Organization address
address: MAX-NAEDER-STRASSE 15 contact info |
DE (DUDERSTADT) | coordinator | 202˙585.00 |
| 2 |
OTTO BOCK HEALTHCARE PRODUCTS GMBH
Organization address
address: KAISERSTRASSE 39 contact info |
AT (WIEN) | participant | 259˙495.00 |
| 3 |
UNIVERSITAETSMEDIZIN GOETTINGEN - GEORG-AUGUST-UNIVERSITAET GOETTINGEN - STIFTUNG OEFFENTLICHEN RECHTS
Organization address
address: Robert-Koch-Strasse 40 contact info |
DE (GOETTINGEN) | participant | 235˙798.00 |
| 4 |
TECHNISCHE UNIVERSITAT BERLIN
Organization address
address: STRASSE DES 17 JUNI 135 contact info |
DE (BERLIN) | participant | 218˙544.00 |
| 5 |
OT BIOELETTRONICA DI BOTTIN ANDREA E MERLO ENRICO & C. S.N.C.
Organization address
address: Via Lancia 62/A contact info |
IT (Torino) | participant | 204˙712.00 |
| 6 |
AALBORG UNIVERSITET
Organization address
address: FREDRIK BAJERS VEJ 5 contact info |
DK (AALBORG) | participant | 31˙272.00 |
Mappa
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Obiettivo del progetto (Objective)
'In spite of decades of research and many capabilities and potentials as well as incremental improvements, advanced human-maschine interfaces based on the electromyogram (EMG) still have a significant distance from professional and commercial applications. This is also and particularly true for myoelectric prosthetic devices. Available commercial myoelectric control systems for prostheses can only control one single degree-of-freedom at a time. However, there is a great need for improved myoelectric control systems. The proposed project will combine European academic excellence in EMG signal processing and pattern recognition, industrial expertise in EMG acquisition, and the clinical and industrial expertise of the market leader in prosthetics. The objective of the proposal is to advance myoelectric control systems that allow simultaneous and intuitive control of several degrees of freedom.'
Introduzione (Teaser)
Prosthetic technology has advanced significantly, but complex movement has not yet been realised. EU-funded researchers worked on advancing signal processing, machine learning and pattern recognition to change the status quo for myoelectric systems.
Descrizione progetto (Article)
Myoelectric prostheses use electrical signals from muscles to control artificial limb movement. Most commercial myoelectric control systems used in prostheses can reliably control only one degree of freedom (DOF) at a time, limiting user acceptance and performance.
Scientists from the EU-supported AMYO (Advanced myoelectric control of prosthetic systems) project with expertise in multidisciplinary fields worked on improving signal acquisition, signal processing and pattern recognition to reliably control multiple DOFs. Their ultimate goal was to ensure commercial viability.
During the first half of the project, the team analysed the current state of the art in myoelectric control of prostheses. Lack of robustness was identified as a major hurdle to commercial application. Building on this result, researchers developed electromyogram electrodes tailored to the residual limbs of amputees to ensure better signal acquisition.
Scientists also developed advanced signal processing methods using neurophysiological modelling and machine learning principles to obtain intuitive, proportional and simultaneous control of two DOFs.
The system was tested on both intact and residual limbs, demonstrating an important increase in performance compared to current myoelectric prostheses. However, test results also highlighted the need for further improved reliability.
To effectively train users, AMYO devised a novel training system based on performance and psychometric measures.
Project outcomes were disseminated via seven scientific publications.
AMYO has considerably increased the reliability and robustness of the myoelectric control system with two DOFs. Further improvements and rapid commercialisation should provide relief for millions of prosthetics users.
A major bonus is that AMYO technology could also be adapted to other assistive devices requiring man-machine interfaces such as orthotics and neurorehabilitation devices.