The dataset is continuously being updated. This version contains segmented raw data for 33 out of 50 subjects.
Zip File containing segmented (Window Length: 101) data: Segmented_Raw_Data
Subject Information (Excel File): Subject Details
The dataset is free and open-source. However, do cite our publications when you use this dataset for research or commercial application:
- S. S. Saha, S. Rahman, M. J. Rasna, T. Hossain, S. Inoue and M. A. R. Ahad. “Supervised and Neural Classifiers for Locomotion Analysis“. Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2018 International Symposium on Wearable Computers Proceedings, ACM, 2018. DOI: 10.1145/3267305.3267524
- S. S. Saha, S. Rahman, M. J. Rasna, T. B. Zahid, A. K. M. M. Islam and M. A. R. Ahad, “Feature Extraction, Performance Analysis and System Design using the DU Mobility Dataset,” in IEEE Access, vol. 6, pp. 44776-44786, 2018. DOI: 10.1109/ACCESS.2018.2865093
- S. S. Saha, S. Rahman, M. J. Rasna, A. K. M. M. Islam, and M. A. R. Ahad, “DU-MD: An Open-Source Human Action Dataset for Ubiquitous Wearable Sensors“, in Proc. Joint 7th Int. Conf. Informatics, Electronics and Vision (ICIEV) and 2nd Int. Conf. Imaging, Vision and Pattern Recognition (IVPR), IEEE, 2018.
For assistance, email at email@example.com
(c) 2018, Swapnil Sayan Saha, Md. Shafizur Rahman, Miftahul Jannat Rasna, A.K.M. Mahfuzul Islam, Dr. Md. Atiqur Rahman Ahad
This work is partially based on the results of a project commissioned by the New Energy and Industrial Technology Development Organization (NEDO). The work is in part supported by FAB Lab DU and IIS, UTokyo.