The SHL Dataset is released in the public domain but credit must be given to the originators of the dataset by citing at least one of the following publications.
If you use the dataset, please cite at least:
 H. Gjoreski, M. Ciliberto, F. J. Ordoñez Morales, D. Roggen, S. Mekki, S. Valentin. “A versatile annotated dataset for multimodal locomotion analytics with mobile devices.” In Proc. ACM Conference on Embedded Networked Sensor Systems. ACM, 2017.
If you use the App, please cite at least:
 M. Ciliberto, F. J. Ordoñez Morales, H. Gjoreski, D. Roggen, S.Mekki, S.Valentin. “High reliability Android application for multidevice multimodal mobile data acquisition and annotation.” In Proc. ACM Conference on Embedded Networked Sensor Systems. ACM, 2017.
We referring to the dataset
- Use at least once the complete name: “The University of Sussex-Huawei Locomotion Dataset” or “The Sussex-Huawei Locomotion Dataset“. You may introduce the acronym of the dataset as well: “The University of Sussex-Huawei Locomotion (SHL) Dataset“.
- Subsequently, you may refer to the dataset with its acronym: “The SHL Dataset“.
- Data organisation and file formats (30.11.2017)
SHL Dataset – Preview
This preview dataset comprises a part of the complete dataset. It includes:
- Data from all three users and all four phone locations
- Three recording-days per user
- 59 hours of annotated recordings, corresponding to 227 hours of data for the 4 phone locations
- All sensor modalities, except for audio
- Version 1 (3 November 2017): initial release
Due to size, the download is split in 3 parts. Part 1 contains the data of user 1 and Matlab demonstration scripts. Part 2 and 3 contain the data of user 2 and 3 respectively.
- Please use 7zip to extract the ZIP files.
- A solution to the VideoReader error in MATLAB under Linux can be found here