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Part of MONSTER: https://arxiv.org/abs/2502.15122.
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, with a sampling rate of 50 Hz [1]. 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).
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