Medical Design Briefs - March 2022 - 28

New Software May Help Neurology Patients Capture
Clinical Data with Their Own Smartphones
The software accurately
detects movements
performed during motor
function assessments.
Johns Hopkins Medicine
Baltimore, MD
New pose estimation software has the
potential to help neurologists and their
patients capture important clinical data
using simple tools such as smartphones
and tablets, according to a study by Johns
Hopkins Medicine, the Kennedy Krieger
Institute, and the University of Maryland.
Human pose estimation is a form of artificial
intelligence that automatically detects
and labels specific landmarks on the
human body, such as elbows and fingers,
from simple images or videos.
To measure the speed, rhythm, and
range of a patient's motor function, neurologists
will often have the patient perform
certain repetitive movements, such
as tapping fingers or opening and closing
hands. An objective assessment of these
tests provides the most accurate insight
into the severity of a patient's condition,
thus better informing treatment decisions.
However, objective motion capture devices
are often expensive or only able to measure
one type of movement. Therefore,
most neurologists must make subjective
assessments of their patients' motor function,
usually by simply watching patients as
they carry out different tasks.
The new Hopkins-led study sought to
find whether pose estimation software
developed by the research team could
track human motion as accurately as manual,
frame-by-frame visual inspections of
video recordings of patients performing
movements.
" Our goal was to develop a fast, inexpensive
and easily accessible method to
objectively measure a patient's movements
across multiple extremities, " says
study lead author Ryan Roemmich,
PhD, an assistant
professor
in
the
department of physical medicine and
rehabilitation at the Johns Hopkins
University School of Medicine and a
human movement scientist at the
Kennedy Krieger Institute.
The research team had 10 healthy subjects
between the ages of 24 and 33 record
smartphone video of themselves perform28
Cov
The
pose estimation software used in the study successfully captured the subjects' movements,
including the opening and closing of hands. (Credit: Dr. Ryan Roemmich)
ing five tasks often assigned to neurology
patients during motor function assessments:
finger taps, hand closures, toe taps,
heel taps, and hand rotations. The subjects
performed each task at four different
speeds. Their movements were tracked
using a freely available human pose estimation
algorithm, then fed into the team's
software for evaluation.
The results showed that across all five
tasks, the software accurately detected
more than 96 percent of the movements
detected by the manual inspection
method. These results held up across several
variables, including location, type of
smartphone used, and method of recording:
Some subjects placed their smartphone
on a
stable
surface and hit
" record, " while others had a family member
or friend hold the device.
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With encouraging results from their
sample of young, healthy people, the
research team's next step is to test the software
on people who require neurological
care. Currently, the team is collecting a
large sample of videos of people with
Parkinson's disease doing the same five
motor function tasks that the healthy subjects
performed.
" We want anyone with a smartphone or
tablet to be able to record video that can
be successfully analyzed by their physician, "
says Roemmich. " With further development
of this pose estimation software,
motor assessments could eventually be
performed and analyzed without the
patient having to leave their home. "
The full study appears in PLOS ONE.
For more information, visit www.hopkinsmedicine.org.
Medical
Design Briefs, March 2022
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Medical Design Briefs - March 2022

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