This custom dataset was created to support gait recognition research using Inertial Measurement Units (IMUs), which capture acceleration, angular velocity, and orientation data from key body locations (e.g., ankles, waist, wrists). It includes recordings from [insert number] participants performing various walking tasks under different conditions, such as normal and fast walking or navigating obstacles. The dataset provides time-series data suitable for both traditional feature-based analysis and deep learning approaches.

Dataset Files

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[1] Fo Hu, "Gait analysis", IEEE Dataport, 2024. [Online]. Available: http://dx.doi.org/10.21227/6xn4-pv39. Accessed: Dec. 05, 2024.
@data{6xn4-pv39-24,
doi = {10.21227/6xn4-pv39},
url = {http://dx.doi.org/10.21227/6xn4-pv39},
author = {Fo Hu },
publisher = {IEEE Dataport},
title = {Gait analysis},
year = {2024} }
TY - DATA
T1 - Gait analysis
AU - Fo Hu
PY - 2024
PB - IEEE Dataport
UR - 10.21227/6xn4-pv39
ER -
Fo Hu. (2024). Gait analysis. IEEE Dataport. http://dx.doi.org/10.21227/6xn4-pv39
Fo Hu, 2024. Gait analysis. Available at: http://dx.doi.org/10.21227/6xn4-pv39.
Fo Hu. (2024). "Gait analysis." Web.
1. Fo Hu. Gait analysis [Internet]. IEEE Dataport; 2024. Available from : http://dx.doi.org/10.21227/6xn4-pv39
Fo Hu. "Gait analysis." doi: 10.21227/6xn4-pv39