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Pediatric Prostheses

Upper limb prostheses for children present with unique challenges. For example, most children that use
prostheses were born with their limb difference and their affected muscles will have never actuated an
intact hand. Therefore, current prosthetic control strategies that derive control signals from these
affected muscles may be dramatically different from adults who typically acquire their limb loss later in
life. Our long-term goal is to develop robust measures of muscle activation in the affected limbs of
children with upper limb deficiencies to understand their capabilities and develop highly functional
prostheses. This work involves close collaborations across departments at UC Davis and with the
Shriners Hospital for Children. Funding sources: NSF Human Centered computing (award #: 2133879)
and Shriners Hospital for Children Clinical Research Program (award #: 79139)

Nerve-Machine Interfaces for Upper Limb Prostheses

Advanced nerve-machine interfaces have progressed to allow individuals to operate artificial limbs by
accessing motor control signals directly from the nerves or brain. Yet these control systems are
inaccessible to most amputees given their highly experimental nature and requirement for invasive
surgically implanted devices. Working with UC Davis Health, our long-term goal is to develop techniques
for more accessible prosthetic nerve-machine interfaces. We are combining standard-of-care surgical
techniques designed to prevent nerve-related pain with advanced prosthesis control systems and
machine learning. Together this provides patients opportunities to control prostheses by ‘thinking’
about moving their missing limbs and even offers possibilities to promote the sense of the prostheses
being a part of the body. Funding sources: UC Davis Early Career Faculty Award for Creativity and
Innovation, and UC Davis Academic Senate.


Sensory-enabled Space Craft Robotics

We are investigating applications of haptic feedback to assist astronauts during spacecraft robotic-arm
operations. This work includes the development of sophisticated sensory feedback systems to relive the
users’ dependence on visual feedback and encode robotic arm trajectory and collision avoidance
information through wearable haptic systems. We are evaluating the effects on human motor learning
and the ability to promote the sense of a robot operating as an extension of the body. Tests include
short term, longitudinal, and long-term isolation studies through NASA’s HERA facilities. Funding
sources: NASA HERO Appendix E: Human Health and Performance Award. (Photo credit: NASA)

Human Machine Integration

The Schofield lab performs broad work aimed to improve user acceptance and promote the seamless
integration of humans and assistive devices. Leveraging techniques in bio-robotic control and feedback,
nerve-machine interfaces, and cognitive-perceptual neurosciences, we are exploring how the combined
actions of human-machine teams may be different from human-human interactions or the action
performed with one’s own body. We use techniques at the interface of mechanical and electrical
engineering, neurosciences and rehabilitation medicine. We are exploring how assistive systems such as
prostheses, virtual reality avatars, and even industrial robotics can communicate with operators to
promote a sense of agency over shared actions and a sense of ownership to blur the perceived lines
between the machine and one’s own body. Funding sources: Meta Platforms Inc.

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