--- tags: - time series - time series classification - monster - HAR license: other pretty_name: UCIActivity --- Part of MONSTER: . |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)*.