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.
Biomechanical gait analysis.
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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.
The database has been compiled by Dr. Fabian Horst of the Institute of Sports Science at Mainz University and Djordje Slijepčević of St. Pölten 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.
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 Slijepčević, 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 Slijepčević.
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.
MEDICA-tradefair.com; Source: Johannes Gutenberg University Mainz