The goal of accel_data is to provide code to download and organize
open source accelerometry data.
In code/R, there are files to analyze data from the IU walking study
(https://physionet.org/content/accelerometry-walk-climb-drive/1.0.0/).
The data were provided by Goldberger et al [^1]. All functions should be
prefixed by iu_*.
To cite this data please use the Physionet citation[^2].
In code/R, there are files to analyze data from the ZJU Gait-Acc
study. The data were provided by Zhang et al[^3]. All functions should
be prefixed by zju_*.
The file located in session_1/subj_039/rec_5/5.txt seems to be
corrupted. The code has a hard-coded section to remove that file from
the main data.
[^1]: Goldberger, A., Amaral, L., Glass, L., Hausdorff, J., Ivanov, P. C., Mark, R., … & Stanley, H. E. (2000). PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals. Circulation [Online]. 101 (23), pp. e215–e220.
[^2]: Karas, M., Urbanek, J., Crainiceanu, C., Harezlak, J., & Fadel, W. (2021). Labeled raw accelerometry data captured during walking, stair climbing and driving (version 1.0.0). PhysioNet. https://doi.org/10.13026/51h0-a262.
[^3]: Yuting Zhang, Gang Pan, Kui Jia, Minlong Lu, Yueming Wang, Zhaohui Wu, “Accelerometer-based Gait Recognition by Sparse Representation of Signature Points with Clusters”, IEEE Transactions on Cybernetics, vol. 45, no. 9, pp. 1864-1875, September 2015.