Tech Briefs Magazine - August 2021 - 46

Health & Biotech
Machine Learning Helps Detect Gait Problems in Multiple
Sclerosis Patients
Gait data and machine learning help to monitor and predict disease progression.
University of Illinois Urbana-Champaign, Champaign
onitoring the progression of multiple
sclerosis-related gait issues can
be challenging in adults over 50 years
old, requiring a clinician to differentiate
between problems related to MS and
other age-related issues. To address this
problem, researchers integrated gait
data and machine learning to advance
the tools used to monitor and predict
disease progression.
M
Multiple sclerosis can present itself in
many ways in the approximately two million
people that it affects globally, and
walking problems are a common symptom.
About half of the patients need
walking assistance within 15 years of on -
set. The researchers sought to determine
the interactions between aging and
concurrent MS disease-related changes
and whether they could differentiate
between the two in older adults with MS.
Machine-learning techniques work particularly
well at spotting complex hidden
changes in performance.
Using an instrumented treadmill, the
team collected gait data - normalized
for body size and demographics - from
20 adults with MS and 20 age-, weight-,
height-, and gender-matched older
adults without MS. The participants
walked at a comfortable pace for up to
75 seconds while specialized software
captured gait events, corresponding
ground reaction forces, and center-ofpressure
positions during each walk.
The team extracted each participant's
characteristic spatial, temporal, and
kinetic features in their strides to examine
variations in gait during each trial.
Changes in various gait features, in -
cluding a data feature called the butterfly
diagram, helped the team detect difWearable,
All-in-One Health Monitor
The soft, stretchy skin patch can monitor cardiovascular signals and multiple biochemical
levels at the same time.
University of California, San Diego
ngineers developed a soft, stretchy skin
patch that can be worn on the neck to
continuously track blood pressure and
heart rate while measuring the wearer's
levels of glucose as well as lactate, alcohol,
or caffeine. It is the first wearable device
that monitors cardiovascular signals and
multiple biochemical levels in the human
body at the same time.
E
This type of wearable could be used by
people with underlying medical conditions
to monitor their own health on a
regular basis. It could also be used for
remote patient monitoring, especially
during the COVID-19 pandemic when
people are minimizing in-person visits to
a healthcare provider.
Completely different sensors are
merged together on a single small platform
as small as a postage stamp. Each
46
Cov
The soft, stretchy patch can monitor the wearer's blood pressure and biochemical levels at the same time.
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Tech Briefs, August 2021
ferences in gait patterns between participants.
The diagram gains its name from
the butterfly-shaped curve created from
the repeated center-of-pressure trajectory
for multiple continuous strides during
a subject's walk and is associated with
critical neurological functions.
Biomechanical systems, such as walking,
are poorly modeled systems, making
it difficult to spot problems in a
clinical setting. The new method ex -
tracted conclusions from data sets that
include many measurements of each
individual but a small number of individuals.
The results of the work make
significant headway in the area of clinical
machine learning-based disease-prediction
strategies.
For more information, contact Professor
Richard Sowers at r-sowers@illinois.edu;
217-333-6246.

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Tech Briefs Magazine - August 2021

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