The viewer is disabled because this dataset repo requires arbitrary Python code execution. Please consider
removing the
loading script
and relying on
automated data support
(you can use
convert_to_parquet
from the datasets library). If this is not possible, please
open a discussion
for direct help.
Part of MONSTER: https://arxiv.org/abs/2502.15122.
| UCIActivity | |
|---|---|
| Category | HAR |
| Num. Examples | 10,299 |
| Num. Channels | 9 |
| Length | 128 |
| Sampling Freq. | 50 Hz |
| Num. Classes | 6 |
| License | Other |
| Citations | [1] |
UCIActivity is a widely recognized benchmark for activity recognition research. It contains sensor readings from 30 participants performing six daily activities: walking, walking upstairs, walking downstairs, sitting, standing, and lying down. The data was collected using a Samsung Galaxy S2 smartphone mounted on the waist of each participant, recording 9 channels of data, with a sampling rate of 50 Hz [1]. The processed dataset contains 10,299 multivariate time series each with length 50 (i.e., one second of data at a sampling rate of 50 Hz). To keep the evaluation fair, we perform subject-wise cross-validation.
[1] Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra, Jorge Luis Reyes-Ortiz, et al. (2013). A public domain dataset for human activity recognition using smartphones. In 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN).
- Downloads last month
- 144