Gait Classification

Donated on 10/14/2020

Gait is considered a biometric criterion. Therefore, we tried to classify people with gait analysis with this gait data set.

Dataset Characteristics

Multivariate

Subject Area

Computer

Associated Tasks

Classification

Attribute Type

Real

# Instances

48

# Attributes

321

Information

Additional Information

This data set was created by calculating the walking parameters of a total of 16 different volunteers, 7 female and 9 male. The volunteers of 16 volunteers ranged between 20 and 34 years old, and their weight ranged from 53 to 95. In order to calculate each walking parameter, people were asked to walk the 30-meter long course for three rounds. The shared file contains X and Y data. X represents gait data and y represents person information for the relevant sample.

Attribute Information

Additional Information

Gait Data consists of the following parameters. Basic Parameters (Speed, Variability, Symmetry), Temporary Parameters (Heel Press Time, Cycle Time, Cadence, Posture, Oscillation, Loading, Foot Press, Thrust, Double Support), Spatial Parameters (Step Length, Step Speed, Peak Angle Speed, Maximum Swing Speed, Rotation Angle, Step Angle, Lift Angle, Swing Width, 3D Path Length), Height Parameters (Maximum Heel Height, Maximum Finger Tip Height, Minimum Finger Tip Height)

Download
0 citations
1667 views

License

By using the UCI Machine Learning Repository, you acknowledge and accept the cookies and privacy practices used by the UCI Machine Learning Repository.

Read Policy