University of Cincinnati College of Engineering and Applied Science | 2025 Dean's Report - Flipbook - Page 9
RESEARCH AIMS TO PREVENT
CONCUSSIONS IN SPORTS
R1
top-tier research institution
E
ric Nauman, professor of biomedical engineering, is studying ways to prevent concussions
in sports, namely football, through testing various models of helmets. In his Human Injury
Research and Regenerative Technologies Lab in UC’s new Bioscience Center, his team explores
conditions like traumatic brain injuries, spinal cord injuries, and musculoskeletal damage. The team
AI IDENTIFIES
CONVERSATION TYPE
developed their own test based on previous research experiences that allowed them to quantify how
Researchers at the University of Cincinnati
much of the impact of a hit is reduced by the helmet. Using a modal hammer that is equipped with
have developed an arti昀椀cial intelligence
sensors to accurately measure applied force, researchers delivered 20 blows by hand at seven impact
system capable of analyzing conversations
points on dummy heads, like those used in vehicle crash testing, both in and out of the helmet.
by monitoring participants’ physiological
responses. A study published in the journal
IEEE Transactions on Affective Computing
200%
research grant funding
increase since 2019
Published in the Journal of Biomedical Engineering, Nauman’s study found that no single design
focused on physiological synchrony, which
demonstrated consistent energy absorption at every part of the helmet. Combining these lab tests
is what happens when people’s autonomic
with 昀椀eld-based impact tracking could improve future assessments and making modest design
nervous system responses become synchro-
changes could have profound bene昀椀ts for players. Nauman also has projects underway to improve
nized when they interact or collaborate.
Physiological synchrony shows up even
construction worker safety on job sites, and a collaboration with Cincinnati Children’s Hospital to
when people are talking over Zoom, said
ensure the safety of premature babies’ heads during helicopter and ambulance transport.
Vesna Novak, associate professor of
electrical engineering.
Novak and lead author, UC doctoral student
Iman Chatterjee, programmed the computer
to recognize types of conversations
143%
growth in the average
participants were having based on a set of
physiological indicators, including skin
conductance, chest and nose respiration,
and an electrocardiogram. As much as 75%
size of research grants
of the time, the AI was able to correctly
awarded since 2019
identify the type of conversation based
only on these cues. The study is one of
the 昀椀rst of its kind to train arti昀椀cial
intelligence how to recognize aspects of
a conversation based on the participants’
physiology alone. The research holds
potential for providing real-time feedback
for educators, therapists and others.
UNIVERSITY OF CINCINNATI | CEAS
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