Metaverse Gait Authentication Dataset (MGAD)

Instructions for Using the MGAD Dataset

1. Downloading the Dataset

• Once the dataset is published, download the CSV file (MGAD.csv) from IEEE DataPort.
• Extract the dataset if it is compressed (e.g., .zip or .tar.gz format).

2. Understanding the Dataset

• Refer to the README file for an overview of the dataset structure and contents.
• The Data Dictionary provides detailed descriptions of each feature in the dataset.

3. Loading the Dataset

You can load the dataset using Python as follows:

 import pandas as pd

# Load the dataset
data = pd.read_csv('MGAD.csv')

# Display first five rows
print(data.head())

4. Preprocessing the Data

• Handle missing values (if any) using standard imputation techniques.
• Normalize numerical features if required for ML models.
• Apply feature scaling (e.g., MinMaxScaler or StandardScaler).

5. Suggested Applications

• Gait-Based User Authentication: Use machine learning models to classify users based on gait patterns.
• Anomaly Detection: Identify unusual gait behaviors using clustering or autoencoders.
• Biomechanics Research: Analyze gait variability and human movement patterns.

6. Citation Guidelines

If you use this dataset in your research, please cite it as follows:

 Sandeep Ravikanti, "Metaverse Gait Authentication Dataset (MGAD)," IEEE DataPort, 2025.


For additional details, refer to the README and Data Dictionary.