Collection of gait analysis data of healthy individuals

Date:
November 3, 2021
Source:
Johannes Gutenberg Universitaet Mainz
Summary:
Gait disorders manifest themselves in various ways. In many cases,
pathological gait patterns are actually accompanying effects or
can even be symptomatic of an underlying disease. For this reason,
biomechanical gait analysis can be a helpful tool when it comes
to diagnosing problems and subsequently treating them. A sports
scientist has now presented the Gutenberg Gait Database, a large
publicly accessible database providing a reference set of data to
be used for the diagnosis and treatment of gait disorders.



FULL STORY ==========================================================================
Gait disorders manifest themselves in various ways: One walks with
small tripping steps, another drags a leg while walking. In one case,
a foot does not roll over the sole of the foot, and in another, a foot
is not lifted sufficiently but is rather dragged across the floor. For
those affected, these disorders may simply have a minor negative
impact on their daily routine while for others they can represent
a major impairment of their quality of life. In many cases, however, pathological gait patterns are actually accompanying effects or can even
be symptomatic of an underlying disease. For this reason, biomechanical
gait analysis can be a helpful tool when it comes to diagnosing problems
and subsequently treating them. "Until now, there has been a worldwide
lack of reference data for healthy persons," emphasized Dr. Fabian Horst
of Johannes Gutenberg University Mainz (JGU). An adequate quantity of
data on the walking characteristics of healthy individuals is needed to
be able to reliably detect and classify pathological gait patterns and
any causative ailments. Dr.

Fabian Horst, a sports scientist, has now presented a database that
will help to close this gap. The Gutenberg Gait Database is the world's
largest publicly accessible database containing relevant information on
healthy volunteers.


========================================================================== Providing data from 350 healthy individuals aged 11 to 64 years The
database has been compiled by Dr. Fabian Horst of the Institute of Sports Science at Mainz University and Djordje Slijepcevic of St. Po"lten
University of Applied Sciences in Austria and comprises data from 350
healthy volunteers who attended the biomechanics lab at JGU over the
past seven years. The database contains ground reaction force (GRF)
and center of pressure (COP) data measured for two consecutive steps,
which were recorded by force plates embedded in the ground over the
entire duration of ground contact of the feet.

"GRF is the force exerted by the feet on the ground during contact -- it
is a standard parameter used throughout the world for the biomechanical analysis of gait," explained Horst. COP provides additional information
on force progression while the progression curve combined with the
data on contact force represents an important indicator with regard to interpreting gait patterns.

For their new database, the researchers put together the results of
350 participants aged 11 to 64 years. "Our data originated from ten
individual studies, so the (pre-)processing of the measured data had to
be standardized before we could merge it," Horst added.

Gutenberg Gait Database now available to all interested users Currently
the world's largest database of healthy individuals, the Gutenberg Gait Database is now publicly accessible and can be used for different aims.

"Orthopedic institutes, for example, can download the data in order
to prepare charts of normative values for use in clinical practice,
while research organizations can gain new insights into human gait,"
said Slijepcevic, outlining some possible applications. The database
provides users with both unprocessed raw data and processed ready-to-use
data. "These data records offer new possibilities for future studies on
human gait, e.g., the application as a reference set for the analysis
of pathological gait patterns, or for automatic classification using
machine learning," write the authors in their article in Scientific Data.

Another feature of the database is that it can be used in combination with GaitRec, the largest dataset of pathological gait patterns. "Combining
these two data sources enables the development of more complex and
robust algorithms for the automatic analysis of gait patterns," confirmed Slijepcevic.

The plan is to continually update the database in future. "The information
we have collated to date is mainly that of younger persons. It would
be desirable to have a more extensive and balanced database with regard
to age and other factors," concluded Dr. Fabian Horst from the Training
and Movement Science division at the JGU Institute of Sports Science.

========================================================================== Story Source: Materials provided by
Johannes_Gutenberg_Universitaet_Mainz. Note: Content may be edited for
style and length.


========================================================================== Journal Reference:
1. Fabian Horst, Djordje Slijepcevic, Marvin Simak, Wolfgang
I. Scho"llhorn.

Gutenberg Gait Database, a ground reaction force database of level
overground walking in healthy individuals. Scientific Data, 2021;
8 (1) DOI: 10.1038/s41597-021-01014-6 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2021/11/211103115456.htm

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