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Part of MONSTER: https://arxiv.org/abs/2502.15122.
WISDM2 extends the original WISDM dataset by collecting data in real-world environments using the Actitracker system. This system was designed for public use and provides a more extensive collection of sensor readings from users performing the same six activities. The dataset contains 2,980,765 samples with three dimensions, and the data was recorded from a larger and more diverse set of participants in naturalistic settings, offering a valuable resource for real-world activity recognition [1]. Both WISDM and WISDM2 are split based on subjects.
[1] Gary Mitchell Weiss and Jeffrey Lockhart. (2012). The impact of personalization on smartphone-based activity recognition. In Workshops at the 26th AAAI Conference on Artificial Intelligence.
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