April 2022

WORLD’S LARGEST COLLECTION OF GAIT ANALYSIS DATA OF HEALTHY INDIVIDUALS PUBLISHED

Biomechanical gait analysis can be a helpful tool when it comes to diagnosing gait problems and subsequently treating them. However, “until now there has been a worldwide lack of reference data for healthy persons,” said Fabian Horst, PhD, of Johannes Gutenberg University Mainz (JGU), Germany. 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. 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 Horst and Djordje Slijepčević of St. Pölten University of Applied Sciences, Austria, and comprises data from 350 healthy volunteers, ages 11 to 64 years old, who attended the biomechanics lab at JGU over the past 7 years. The database contains ground reaction force (GRF) and center of pressure (COP) data measured for 2 consecutive steps, which were recorded by force plates embedded in the ground over the entire duration of ground contact of the feet. “Our data originated from 10 individual studies, so the (pre-)processing of the measured data had to be standardized before we could merge it,” Horst added.

The Gutenberg Gait Database, which is now publicly accessible, provides users with both unprocessed raw data and processed ready-to-use data. According to Horst and Slijepčević , these data records offer new possibilities for future studies on human gait, eg, the application as a reference set for the analysis of pathological gait patterns, or for automatic classification using machine learning.

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,” said Slijepčević .

The plan is to continually update the database, as well as to include more extensive and balanced data with regard to age and other factors.

To access the database, visit https://springernature.figshare.com/collections/Gutenberg_Gait_Database_A_ground_reaction_force_database_of_level_overground_walking_in_healthy_individuals/5311538/1.

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