Nav: Home

A smart artificial hand for amputees merges user and robotic control

September 11, 2019

EPFL scientists are developing new approaches for improved control of robotic hands - in particular for amputees - that combines individual finger control and automation for improved grasping and manipulation. This interdisciplinary proof-of-concept between neuroengineering and robotics was successfully tested on three amputees and seven healthy subjects. The results are published in today's issue of Nature Machine Intelligence.

The technology merges two concepts from two different fields. Implementing them both together had never been done before for robotic hand control, and contributes to the emerging field of shared control in neuroprosthetics.

One concept, from neuroengineering, involves deciphering intended finger movement from muscular activity on the amputee's stump for individual finger control of the prosthetic hand which has never before been done. The other, from robotics, allows the robotic hand to help take hold of objects and maintain contact with them for robust grasping.

"When you hold an object in your hand, and it starts to slip, you only have a couple of milliseconds to react," explains Aude Billard who leads EPFL's Learning Algorithms and Systems Laboratory. "The robotic hand has the ability to react within 400 milliseconds. Equipped with pressure sensors all along the fingers, it can react and stabilize the object before the brain can actually perceive that the object is slipping. "

How shared control works

The algorithm first learns how to decode user intention and translates this into finger movement of the prosthetic hand. The amputee must perform a series of hand movements in order to train the algorithm that uses machine learning. Sensors placed on the amputee's stump detect muscular activity, and the algorithm learns which hand movements correspond to which patterns of muscular activity. Once the user's intended finger movements are understood, this information can be used to control individual fingers of the prosthetic hand.

"Because muscle signals can be noisy, we need a machine learning algorithm that extracts meaningful activity from those muscles and interprets them into movements," says Katie Zhuang first author of the publication.

Next, the scientists engineered the algorithm so that robotic automation kicks in when the user tries to grasp an object. The algorithm tells the prosthetic hand to close its fingers when an object is in contact with sensors on the surface of the prosthetic hand. This automatic grasping is an adaptation from a previous study for robotic arms designed to deduce the shape of objects and grasp them based on tactile information alone, without the help of visual signals.

Many challenges remain to engineer the algorithm before it can be implemented in a commercially available prosthetic hand for amputees. For now, the algorithm is still being tested on a robot provided by an external party.

"Our shared approach to control robotic hands could be used in several neuroprosthetic applications such as bionic hand prostheses and brain-to-machine interfaces, increasing the clinical impact and usability of these devices," Silvestro Micera, EPFL's Bertarelli Foundation Chair in Translational Neuroengineering, and Professor of Bioelectronics at Scuola Superiore Sant'Anna.
-end-


Ecole Polytechnique Fédérale de Lausanne

Related Algorithm Articles:

QUT algorithm could quash Twitter abuse of women
Online abuse targeting women, including threats of harm or sexual violence, has proliferated across all social media platforms but QUT researchers have developed a sophisticated statistical model to identify misogynistic content and help drum it out of the Twittersphere.
New learning algorithm should significantly expand the possible applications of AI
The e-prop learning method developed at Graz University of Technology forms the basis for drastically more energy-efficient hardware implementations of Artificial Intelligence.
Algorithm predicts risk for PTSD after traumatic injury
With high precision, a new algorithm predicts which patients treated for traumatic injuries in the emergency department will later develop posttraumatic stress disorder.
New algorithm uses artificial intelligence to help manage type 1 diabetes
Researchers and physicians at Oregon Health & Science University have designed a method to help people with type 1 diabetes better manage their glucose levels.
A new algorithm predicts the difficulty in fighting fire
The tool completes previous studies with new variables and could improve the ability to respond to forest fires.
New algorithm predicts optimal materials among all possible compounds
Skoltech researchers have offered a solution to the problem of searching for materials with required properties among all possible combinations of chemical elements.
New algorithm to help process biological images
Skoltech researchers have presented a new biological image processing method that accurately picks out specific biological objects in complex images.
Skoltech scientists break Google's quantum algorithm
In the near term, Google has devised new quantum enhanced algorithms that operate in the presence of realistic noise.
The most human algorithm
A team from the research group SEES:lab of the Department of Chemical Engineering of the Universitat Rovira I Virgili and ICREA has made a breakthrough with the development of a new algorithm that makes more accurate predictions and generates mathematical models that also make it possible to understand these predictions.
Algorithm turns cancer gene discovery on its head
Prediction method could help personalize cancer treatments and reveal new drug targets.
More Algorithm News and Algorithm Current Events

Trending Science News

Current Coronavirus (COVID-19) News

Top Science Podcasts

We have hand picked the top science podcasts of 2020.
Now Playing: TED Radio Hour

Debbie Millman: Designing Our Lives
From prehistoric cave art to today's social media feeds, to design is to be human. This hour, designer Debbie Millman guides us through a world made and remade–and helps us design our own paths.
Now Playing: Science for the People

#574 State of the Heart
This week we focus on heart disease, heart failure, what blood pressure is and why it's bad when it's high. Host Rachelle Saunders talks with physician, clinical researcher, and writer Haider Warraich about his book "State of the Heart: Exploring the History, Science, and Future of Cardiac Disease" and the ails of our hearts.
Now Playing: Radiolab

Insomnia Line
Coronasomnia is a not-so-surprising side-effect of the global pandemic. More and more of us are having trouble falling asleep. We wanted to find a way to get inside that nighttime world, to see why people are awake and what they are thinking about. So what'd Radiolab decide to do?  Open up the phone lines and talk to you. We created an insomnia hotline and on this week's experimental episode, we stayed up all night, taking hundreds of calls, spilling secrets, and at long last, watching the sunrise peek through.   This episode was produced by Lulu Miller with Rachael Cusick, Tracie Hunte, Tobin Low, Sarah Qari, Molly Webster, Pat Walters, Shima Oliaee, and Jonny Moens. Want more Radiolab in your life? Sign up for our newsletter! We share our latest favorites: articles, tv shows, funny Youtube videos, chocolate chip cookie recipes, and more. Support Radiolab by becoming a member today at Radiolab.org/donate.