Design World

  • Home
  • Technologies
    • 3D CAD
    • Electronics • electrical
    • Fastening & Joining
    • Factory automation
    • Linear Motion
    • Motion Control
    • Test & Measurement
    • Sensors
    • Fluid power
  • Learn
    • Ebooks / Tech Tips
    • Engineering Week
    • Future of Design Engineering
    • MC² Motion Control Classrooms
    • Podcasts
    • Videos
    • Webinars
  • LEAP AWARDS
  • Leadership
    • 2022 Voting
    • 2021 Winners
  • Design Guide Library
  • Resources
    • 3D Cad Models
      • PARTsolutions
      • TraceParts
    • Digital Issues
      • Design World
      • EE World
    • Women in Engineering
  • Supplier Listings

Smart Walk Assist Improves Rehabilitation

By Ecole Polytechnique Federale de Lausanne | July 25, 2017

Share

Scientists from NCCR Robotics at EPFL and at the Lausanne University Hospital (CHUV) developed an algorithm that adjusts how a mobile harness, suspended from the ceiling, assists patients suffering from spinal cord injury or stroke. In a clinical study with over 30 patients, the scientists showed that the patients wearing the smart walking assist immediately improved their locomotor abilities, enabling them to perform activities of daily living that would not be possible without the support. The results are published in the July 20th edition of Science Translational Medicine.

In rehabilitation involving neurological disorders or injury, teaching the nervous system to adopt the correct movements is a major challenge. The loss of muscle mass that prevents people from walking correctly, as does the neurological wiring that needs to be trained to relearn proper posture and walking movements. As long as the patient repeats unnatural movements, the nervous system will keep on remembering the flawed motion.

The idea of the smart walking assist is to promote natural walking in patients so that the nervous system learns how to walk normally again. Body-weight support systems are already used in rehabilitation. In this latest study, it is the first time such a support system operates in conjunction with an algorithm that tailors the assistance to each and every patient.

The algorithm is based on careful monitoring of the patient as he or she moves, including parameters like leg movement, length of stride and muscle activity. Based on these observations, the algorithm determines the forces to be applied to the trunk of the body, via the smart walking assist, in order to enable natural walking patterns. Concretely, this translates into either relieving the patient of his or her own weight, pushing the patient forwards or backwards, to one side or the other, or a combination of the above, for a more natural posture.

“I expect that this platform will play a critical role in the rehabilitation of walking for people with neurological disorders,” says Grégoire Courtine, neuroscientist at EPFL and at the Lausanne University Hospital.

The research results triggered the development of the next-generation smart walking assist device, termed RYSEN, which is performed under the umbrella of EUROSTARS, a European Union subsidy project. The collaboration is European with partners in Switzerland and the Netherlands, including EPFL, Technical University of Delft, Motek, the EPFL spin-off G-Therapeutics and the clinical partner SUVA in Sion.

Quotes from other researchers.

Joachim von Zitzewitz, co-inventor of the RYSEN and project manager of the Eurostars project: “It is thrilling to see how a scientific idea materializes into a new medical product. I am looking forward to see patients benefiting from this research.”

Jocelyne Bloch, associate professor at the Lausanne University Hospital Neurosurgery Department : “This is a smart, discreet and efficient assistance that will aid rehabilitation of many persons with neurological disorders.”


Filed Under: M2M (machine to machine)

 

Related Articles Read More >

Part 6: IDE and other software for connectivity and IoT design work
Part 4: Edge computing and gateways proliferate for industrial machinery
Part 3: Trends in Ethernet, PoE, IO-Link, HIPERFACE, and single-cable solutions
Machine Learning for Sensors

DESIGN GUIDE LIBRARY

“motion

Enews Sign Up

Motion Control Classroom

Design World Digital Edition

cover

Browse the most current issue of Design World and back issues in an easy to use high quality format. Clip, share and download with the leading design engineering magazine today.

EDABoard the Forum for Electronics

Top global problem solving EE forum covering Microcontrollers, DSP, Networking, Analog and Digital Design, RF, Power Electronics, PCB Routing and much more

EDABoard: Forum for electronics

Sponsored Content

  • Renishaw next-generation FORTiS™ enclosed linear encoders offer enhanced metrology and reliability for machine tools
  • WAGO’s smartDESIGNER Online Provides Seamless Progression for Projects
  • Epoxy Certified for UL 1203 Standard
  • The Importance of Industrial Cable Resistance to Chemicals and Oils
  • Optimize, streamline and increase production capacity with pallet-handling conveyor systems
  • Global supply needs drive increased manufacturing footprint development

Design World Podcasts

June 12, 2022
How to avoid over engineering a part
See More >
Engineering Exchange

The Engineering Exchange is a global educational networking community for engineers.

Connect, share, and learn today »

Design World
  • Advertising
  • About us
  • Contact
  • Manage your Design World Subscription
  • Subscribe
  • Design World Digital Network
  • Engineering White Papers
  • LEAP AWARDS

Copyright © 2022 WTWH Media LLC. All Rights Reserved. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of WTWH Media
Privacy Policy | Advertising | About Us

Search Design World

  • Home
  • Technologies
    • 3D CAD
    • Electronics • electrical
    • Fastening & Joining
    • Factory automation
    • Linear Motion
    • Motion Control
    • Test & Measurement
    • Sensors
    • Fluid power
  • Learn
    • Ebooks / Tech Tips
    • Engineering Week
    • Future of Design Engineering
    • MC² Motion Control Classrooms
    • Podcasts
    • Videos
    • Webinars
  • LEAP AWARDS
  • Leadership
    • 2022 Voting
    • 2021 Winners
  • Design Guide Library
  • Resources
    • 3D Cad Models
      • PARTsolutions
      • TraceParts
    • Digital Issues
      • Design World
      • EE World
    • Women in Engineering
  • Supplier Listings