monster-monash/UCIActivity

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 21^st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN).