How we can better link mind and machine

July 28, 2022
A user's legs walking with a powered ankle exoskeleton on a treadmill
A user demonstrates walking with a lower-body exoskeleton. In a new study, powered exoskeleton users had trouble incorporating instructional haptic feedback cues, informing how future human-machine interaction must be designed. Photo: Brenda Ahearn/University of Michigan, College of Engineering, Communications and Marketing

A team led by University of Michigan researchers recently tested how exoskeleton users responded to the task of matching haptic feedback to the timing of each footstep. The team found that the haptic cues added mental workload, causing less effective use of the exoskeleton, and demonstrated the hurdles in future human-machine design.

“When we introduce haptic feedback while walking with an exoskeleton, we usually intend for the user to understand and maintain coordination with the exoskeleton,” said Man I (Maggie) Wu, a robotics PhD student.

“We discovered that the exoskeleton actually introduces a competing mental load. We really need to understand how this affects the user while they attempt to complete tasks.”

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U-M, Humotech partner to bring open-source bionic leg to research labs

December 16, 2021

The open-source, artificially intelligent prosthetic leg designed by researchers at the University of Michigan will be brought to the research market by Humotech, a Pittsburgh-based assistive technology company.

The goal of the collaboration is to speed the development of control software for robotic prosthetic legs, which have the potential to provide the power and natural gait of a human leg to prosthetic users.

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$1.7M to build everyday exoskeletons to assist with lifting, walking and climbing stairs

October 4, 2021
A model of the powered exoskeleton on the hip, knee and ankle joints. The modular system will be able to assist any combination of these joints, no matter the activity. Credit: Locomotor Control Systems Laboratory, University of Michigan

In an effort to bring robotic assistance to workers, the elderly and more, a University of Michigan team is developing a new type of powered exoskeleton for lower limbs—funded by $1.7 million from the National Institutes of Health.

One in eight Americans faces a mobility disability, with serious difficulty walking or climbing stairs, but a robotic solution could be far less bulky than sci-fi’s full-body suits. The U-M team plans to develop a modular, powered exoskeleton system that could be used on one or multiple joints of the legs. The three-year project will first study workers who lift and lower objects and the elderly who have lost mobility with age. In future work, the team would like to include people with other disabilities.

“Imagine adding a small motor to a bicycle—the rider still pedals, but there’s that extra power to get up hills without breaking too much of a sweat,” said project lead Robert Gregg, member of the Robotics Institute and associate professor of electrical and computer engineering.

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Next steps of the Open Source Leg

October 13, 2020
An open source leg on a table with wires and tools
Alejandro Azocar puts the finishing connections together before testing an open-source robotic leg designed by Elliott Rouse. Photo: Robert Coelius, Michigan Engineering

A new paper on the Open Source Leg, an artificially-intelligent bionic prosthetic leg developed by University of Michigan researchers, was recently published in Nature Biomedical Engineering.

The open-source project, launched publicly last year, is meant to ease the research of controls for prostheses by offering an accessible, comparable, and universal platform available to a broad array of scientists and engineers.

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Brain interface pioneers find meaningful signal in the grey matter noise

July 27, 2020
Drastically reducing the power and computation needed to identify our intentions, researchers open up a future of advanced therapies and machines enabled by our thoughts.

By tuning into a subset of brain waves, University of Michigan researchers have dramatically reduced the power requirements of neural interfaces while improving their accuracy. This discovery could lead to long-lasting brain implants that can both treat neurological diseases and enable mind-controlled prosthetics and machines.

The team, led by Cynthia Chestek, associate professor of biomedical engineering and core faculty at the Robotics Institute, estimated a 90% drop in power consumption of neural interfaces by utilizing their approach.

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