First workshop on Present and future of non-invasive PNS-Machine Interfaces
hosted by ICORR 2013, Seattle, WA, June 2013.
Organised by Claudio Castellini, Ph.D. (Robotics and Mechatronics Center, DLR – German Aerospace Center) and Panagiotis K. Artemiadis, Ph.D. (Ira A. Fulton School of Engineerings, Arizona State University, USA)
Statement of the workshop
This workshop is about human-machine interfaces which connect non-invasively to the peripheral nervous system (PNS-MIs), surface electromyography (sEMG) being the paradigmatic PMI. sEMG is in use since the 60s to proportionally control single-DoFs hand prostheses. It involves neither surgery nor hospitalisation; its signal remains rich in information even decades after an amputation, and provides clearer signals than brain-computer interfaces such as, e.g., electroencephalography.
Since then literally dozens different approaches have been applied to sEMG to decode an amputee’s intentions, but none of them have as yet made it to the clinics: as a PMI, sEMG has revealed to be unreliable, badly conditioned, subject to change with time, fatigue and sweat. No valid alternatives to sEMG are in sight, and nevertheless, dexterous prosthetic hands are now appearing on the market, demanding ever better control by the patient.
So, how can we bridge this gap? We address four fundamental sub-problems:
1. what is wrong with the current approach? why do clinicians not use it?
2. how can we better use sEMG?
3. what alternative, radically new solutions are available, if any?
4. what are the benefits of sharing control between the human subject and the prosthesis?
The workshop revolves around the four themes spanned by the above questions.
Merkur Alimusaj, Rüdiger Rupp, University of Heidelberg, Germany
S-EMG in upper extremity Prosthetics: Where are we?
Todd Kuiken, Levi Hargrove, Rehabilitation Institute of Chicago, USA
Bridging the Gap: Transitioning Neural Control Systems from the Research Lab to the Clinic
Eric Scheme, Kevin Englehart, University of New Brunswick, Canada
Enhancing the Clinical Reliability of Pattern Recognition Based Myoelectric Control
Arjan Gijsberts, Barbara Caputo, IDIAP, Martigny, Switzerland
The Ninapro Project: Database, Benchmarks and Challenges
Patrick M. Pilarski, University of Alberta, Canada
Learning and Using Contextual Information in the Control of Assistive Devices
Claudio Castellini, David Sierra González, DLR, Oberpfaffenhofen, Germany
Using Ultrasound Imaging as a novel PNS-Machine Interface
William Craelius, Michael Wininger, Rutgers University, USA
Inherent Limitations of Surface Electromyography for Controlling Artificial Hands
Dario Farina, Marko Markovic, Strahinja Dosen, University of Göttingen, Germany
Myocontrol integrated with computer vision for dexterous use of active prostheses
Panagiotis Artemiadis, Arizona State University, USA
Advances in EMG control interfaces: Beyond decoding, beyond subject-specificity
Antonio Bicchi, Sasha B. Godfrey, Arash Ajoudani, IIT, Italy
Tele-impedance control of a hand intended for prosthetic applications